Cultural macroevolution on neighbor graphs : vertical and horizontal transmission among Western North American Indian societies.

PubMed

Towner, Mary C; Grote, Mark N; Venti, Jay; Borgerhoff Mulder, Monique

2012-09-01

What are the driving forces of cultural macroevolution, the evolution of cultural traits that characterize societies or populations? This question has engaged anthropologists for more than a century, with little consensus regarding the answer. We develop and fit autologistic models, built upon both spatial and linguistic neighbor graphs, for 44 cultural traits of 172 societies in the Western North American Indian (WNAI) database. For each trait, we compare models including or excluding one or both neighbor graphs, and for the majority of traits we find strong evidence in favor of a model which uses both spatial and linguistic neighbors to predict a trait's distribution. Our results run counter to the assertion that cultural trait distributions can be explained largely by the transmission of traits from parent to daughter populations and are thus best analyzed with phylogenies. In contrast, we show that vertical and horizontal transmission pathways can be incorporated in a single model, that both transmission modes may indeed operate on the same trait, and that for most traits in the WNAI database, accounting for only one mode of transmission would result in a loss of information.

AVNM: A Voting based Novel Mathematical Rule for Image Classification.

PubMed

Vidyarthi, Ankit; Mittal, Namita

2016-12-01

In machine learning, the accuracy of the system depends upon classification result. Classification accuracy plays an imperative role in various domains. Non-parametric classifier like K-Nearest Neighbor (KNN) is the most widely used classifier for pattern analysis. Besides its easiness, simplicity and effectiveness characteristics, the main problem associated with KNN classifier is the selection of a number of nearest neighbors i.e. "k" for computation. At present, it is hard to find the optimal value of "k" using any statistical algorithm, which gives perfect accuracy in terms of low misclassification error rate. Motivated by the prescribed problem, a new sample space reduction weighted voting mathematical rule (AVNM) is proposed for classification in machine learning. The proposed AVNM rule is also non-parametric in nature like KNN. AVNM uses the weighted voting mechanism with sample space reduction to learn and examine the predicted class label for unidentified sample. AVNM is free from any initial selection of predefined variable and neighbor selection as found in KNN algorithm. The proposed classifier also reduces the effect of outliers. To verify the performance of the proposed AVNM classifier, experiments are made on 10 standard datasets taken from UCI database and one manually created dataset. The experimental result shows that the proposed AVNM rule outperforms the KNN classifier and its variants. Experimentation results based on confusion matrix accuracy parameter proves higher accuracy value with AVNM rule. The proposed AVNM rule is based on sample space reduction mechanism for identification of an optimal number of nearest neighbor selections. AVNM results in better classification accuracy and minimum error rate as compared with the state-of-art algorithm, KNN, and its variants. The proposed rule automates the selection of nearest neighbor selection and improves classification rate for UCI dataset and manually created dataset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Interactions of galaxies outside clusters and massive groups

NASA Astrophysics Data System (ADS)

Yadav, Jaswant K.; Chen, Xuelei

2018-06-01

We investigate the dependence of physical properties of galaxies on small- and large-scale density environment. The galaxy population consists of mainly passively evolving galaxies in comparatively low-density regions of Sloan Digital Sky Survey (SDSS). We adopt (i) local density, ρ _{20}, derived using adaptive smoothing kernel, (ii) projected distance, r_p, to the nearest neighbor galaxy and (iii) the morphology of the nearest neighbor galaxy as various definitions of environment parameters of every galaxy in our sample. In order to detect long-range interaction effects, we group galaxy interactions into four cases depending on morphology of the target and neighbor galaxies. This study builds upon an earlier study by Park and Choi (2009) by including improved definitions of target and neighbor galaxies, thus enabling us to better understand the effect of "the nearest neighbor" interaction on the galaxy. We report that the impact of interaction on galaxy properties is detectable at least up to the pair separation corresponding to the virial radius of (the neighbor) galaxies. This turns out to be mostly between 210 and 360 h^{-1}kpc for galaxies included in our study. We report that early type fraction for isolated galaxies with r_p > r_{vir,nei} is almost ignorant of the background density and has a very weak density dependence for closed pairs. Star formation activity of a galaxy is found to be crucially dependent on neighbor galaxy morphology. We find star formation activity parameters and structure parameters of galaxies to be independent of the large-scale background density. We also exhibit that changing the absolute magnitude of the neighbor galaxies does not affect significantly the star formation activity of those target galaxies whose morphology and luminosities are fixed.

Elliptic Painlevé equations from next-nearest-neighbor translations on the E_8^{(1)} lattice

NASA Astrophysics Data System (ADS)

Joshi, Nalini; Nakazono, Nobutaka

2017-07-01

The well known elliptic discrete Painlevé equation of Sakai is constructed by a standard translation on the E_8(1) lattice, given by nearest neighbor vectors. In this paper, we give a new elliptic discrete Painlevé equation obtained by translations along next-nearest-neighbor vectors. This equation is a generic (8-parameter) version of a 2-parameter elliptic difference equation found by reduction from Adler’s partial difference equation, the so-called Q4 equation. We also provide a projective reduction of the well known equation of Sakai.

MMDB: Entrez’s 3D-structure database

PubMed Central

Wang, Yanli; Anderson, John B.; Chen, Jie; Geer, Lewis Y.; He, Siqian; Hurwitz, David I.; Liebert, Cynthia A.; Madej, Thomas; Marchler, Gabriele H.; Marchler-Bauer, Aron; Panchenko, Anna R.; Shoemaker, Benjamin A.; Song, James S.; Thiessen, Paul A.; Yamashita, Roxanne A.; Bryant, Stephen H.

2002-01-01

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez’s 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez’s search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez’s Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure. PMID:11752307

Long-term effect of September 11 on the political behavior of victims’ families and neighbors

PubMed Central

Hersh, Eitan D.

2013-01-01

This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims’ families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become—and have stayed—significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis. PMID:24324145

Long-term effect of September 11 on the political behavior of victims' families and neighbors.

PubMed

Hersh, Eitan D

2013-12-24

This article investigates the long-term effect of September 11, 2001 on the political behaviors of victims' families and neighbors. Relative to comparable individuals, family members and residential neighbors of victims have become--and have stayed--significantly more active in politics in the last 12 years, and they have become more Republican on account of the terrorist attacks. The method used to demonstrate these findings leverages the random nature of the terrorist attack to estimate a causal effect and exploits new techniques to link multiple, individual-level, governmental databases to measure behavioral change without relying on surveys or aggregate analysis.

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

NASA Technical Reports Server (NTRS)

Robison-Cox, J. F.; Bateson, M. M.; Ward, D. M.

1995-01-01

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

A nearest neighbor approach for automated transporter prediction and categorization from protein sequences.

PubMed

Li, Haiquan; Dai, Xinbin; Zhao, Xuechun

2008-05-01

Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework. Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB.

A guidance law for hypersonic descent to a point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisler, G.R.; Hull, D.G.

1992-05-01

A neighboring external control problem is formulated for a hypersonic glider to execute a maximum-terminal-velocity descent to a stationary target. The resulting two-part, feedback control scheme initially solves a nonlinear algebraic problem to generate a nominal trajectory to the target altitude. Secondly, a neighboring optimal path computation about the nominal provides a lift and side-force perturbations necessary to achieve the target downrange and crossrange. On-line feedback simulations of the proposed scheme and a form of proportional navigation are compared with an off-line parameter optimization method. The neighboring optimal terminal velocity compares very well with the parameter optimization solution and ismore » far superior to proportional navigation. 8 refs.« less

A guidance law for hypersonic descent to a point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisler, G.R.; Hull, D.G.

1992-01-01

A neighboring external control problem is formulated for a hypersonic glider to execute a maximum-terminal-velocity descent to a stationary target. The resulting two-part, feedback control scheme initially solves a nonlinear algebraic problem to generate a nominal trajectory to the target altitude. Secondly, a neighboring optimal path computation about the nominal provides a lift and side-force perturbations necessary to achieve the target downrange and crossrange. On-line feedback simulations of the proposed scheme and a form of proportional navigation are compared with an off-line parameter optimization method. The neighboring optimal terminal velocity compares very well with the parameter optimization solution and ismore » far superior to proportional navigation. 8 refs.« less

Belowground neighbor perception in Arabidopsis thaliana studied by transcriptome analysis: roots of Hieracium pilosella cause biotic stress

PubMed Central

Schmid, Christoph; Bauer, Sibylle; Müller, Benedikt; Bartelheimer, Maik

2013-01-01

Root-root interactions are much more sophisticated than previously thought, yet the mechanisms of belowground neighbor perception remain largely obscure. Genome-wide transcriptome analyses allow detailed insight into plant reactions to environmental cues. A root interaction trial was set up to explore both morphological and whole genome transcriptional responses in roots of Arabidopsis thaliana in the presence or absence of an inferior competitor, Hieracium pilosella. Neighbor perception was indicated by Arabidopsis roots predominantly growing away from the neighbor (segregation), while solitary plants placed more roots toward the middle of the pot. Total biomass remained unaffected. Database comparisons in transcriptome analysis revealed considerable similarity between Arabidopsis root reactions to neighbors and reactions to pathogens. Detailed analyses of the functional category “biotic stress” using MapMan tools found the sub-category “pathogenesis-related proteins” highly significantly induced. A comparison to a study on intraspecific competition brought forward a core of genes consistently involved in reactions to neighbor roots. We conclude that beyond resource depletion roots perceive neighboring roots or their associated microorganisms by a relatively uniform mechanism that involves the strong induction of pathogenesis-related proteins. In an ecological context the findings reveal that belowground neighbor detection may occur independently of resource depletion, allowing for a time advantage for the root to prepare for potential interactions. PMID:23967000

Spatial correlations in polydisperse, frictionless, two-dimensional packings

NASA Astrophysics Data System (ADS)

O'Donovan, C. B.; Möbius, M. E.

2011-08-01

We investigate next-nearest-neighbor correlations of the contact number in simulations of polydisperse, frictionless packings in two dimensions. We find that disks with few contacting neighbors are predominantly in contact with disks that have many neighbors and vice versa at all packing fractions. This counterintuitive result can be explained by drawing a direct analogy to the Aboav-Weaire law in cellular structures. We find an empirical one parameter relation similar to the Aboav-Weaire law that satisfies an exact sum rule constraint. Surprisingly, there are no correlations in the radii between neighboring particles, despite correlations between contact number and radius.

CLEARPOND: Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities

PubMed Central

Marian, Viorica; Bartolotti, James; Chabal, Sarah; Shook, Anthony

2012-01-01

Past research has demonstrated cross-linguistic, cross-modal, and task-dependent differences in neighborhood density effects, indicating a need to control for neighborhood variables when developing and interpreting research on language processing. The goals of the present paper are two-fold: (1) to introduce CLEARPOND (Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities), a centralized database of phonological and orthographic neighborhood information, both within and between languages, for five commonly-studied languages: Dutch, English, French, German, and Spanish; and (2) to show how CLEARPOND can be used to compare general properties of phonological and orthographic neighborhoods across languages. CLEARPOND allows researchers to input a word or list of words and obtain phonological and orthographic neighbors, neighborhood densities, mean neighborhood frequencies, word lengths by number of phonemes and graphemes, and spoken-word frequencies. Neighbors can be defined by substitution, deletion, and/or addition, and the database can be queried separately along each metric or summed across all three. Neighborhood values can be obtained both within and across languages, and outputs can optionally be restricted to neighbors of higher frequency. To enable researchers to more quickly and easily develop stimuli, CLEARPOND can also be searched by features, generating lists of words that meet precise criteria, such as a specific range of neighborhood sizes, lexical frequencies, and/or word lengths. CLEARPOND is freely-available to researchers and the public as a searchable, online database and for download at http://clearpond.northwestern.edu. PMID:22916227

Diversity of neighborhoods promotes cooperation in evolutionary social dilemmas

NASA Astrophysics Data System (ADS)

Ma, Yongjuan; Lu, Jun; Shi, Lei

2017-02-01

Explaining the evolution of cooperative behavior is one of the most important and interesting problems in a myriad of disciplines, such as evolutionary biology, mathematics, statistical physics, social science and economics Up to now, there have been a great number of works aiming to this issue with the help of evolutionary game theory. However, vast majority of existing literatures simply assume that the interaction neighborhood and replacement neighborhood are symmetric, which seems inconsistent with real-world cases. In this paper, we consider the asymmetrical neighborhood: player of type A, whose factor is controlled by a parameter τ, has four interaction neighbors and four replacement neighbors, while player of type B, whose factor is controlled by a parameter 1 - τ, possess eight interaction neighbors and four replacement neighbors. By means of numerous Monte Carlo simulations, we found that middle τ can make the cooperation reach the highest level While for this finding, its robustness can be further validated in more games.

Interacting Effects Induced by Two Neighboring Pits Considering Relative Position Parameters and Pit Depth

PubMed Central

Huang, Yongfang; Gang, Tieqiang; Chen, Lijie

2017-01-01

For pre-corroded aluminum alloy 7075-T6, the interacting effects of two neighboring pits on the stress concentration are comprehensively analyzed by considering various relative position parameters (inclination angle θ and dimensionless spacing parameter λ) and pit depth (d) with the finite element method. According to the severity of the stress concentration, the critical corrosion regions, bearing high susceptibility to fatigue damage, are determined for intersecting and adjacent pits, respectively. A straightforward approach is accordingly proposed to conservatively estimate the combined stress concentration factor induced by two neighboring pits, and a concrete application example is presented. It is found that for intersecting pits, the normalized stress concentration factor Ktnor increases with the increase of θ and λ and always reaches its maximum at θ = 90°, yet for adjacent pits, Ktnor decreases with the increase of λ and the maximum value appears at a slight asymmetric location. The simulations reveal that Ktnor follows a linear and an exponential relationship with the dimensionless depth parameter Rd for intersecting and adjacent cases, respectively. PMID:28772758

Social aggregation in pea aphids: experiment and random walk modeling.

PubMed

Nilsen, Christa; Paige, John; Warner, Olivia; Mayhew, Benjamin; Sutley, Ryan; Lam, Matthew; Bernoff, Andrew J; Topaz, Chad M

2013-01-01

From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid's nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control.

Understanding the mechanisms of solid-water reactions through analysis of surface topography.

PubMed

Bandstra, Joel Z; Brantley, Susan L

2015-12-01

The topography of a reactive surface contains information about the reactions that form or modify the surface and, therefore, it should be possible to characterize reactivity using topography parameters such as surface area, roughness, or fractal dimension. As a test of this idea, we consider a two-dimensional (2D) lattice model for crystal dissolution and examine a suite of topography parameters to determine which may be useful for predicting rates and mechanisms of dissolution. The model is based on the assumption that the reactivity of a surface site decreases with the number of nearest neighbors. We show that the steady-state surface topography in our model system is a function of, at most, two variables: the ratio of the rate of loss of sites with two neighbors versus three neighbors (d(2)/d(3)) and the ratio of the rate of loss of sites with one neighbor versus three neighbors (d(1)/d(3)). This means that relative rates can be determined from two parameters characterizing the topography of a surface provided that the two parameters are independent of one another. It also means that absolute rates cannot be determined from measurements of surface topography alone. To identify independent sets of topography parameters, we simulated surfaces from a broad range of d(1)/d(3) and d(2)/d(3) and computed a suite of common topography parameters for each surface. Our results indicate that the fractal dimension D and the average spacing between steps, E[s], can serve to uniquely determine d(1)/d(3) and d(2)/d(3) provided that sufficiently strong correlations exist between the steps. Sufficiently strong correlations exist in our model system when D>1.5 (which corresponds to D>2.5 for real 3D reactive surfaces). When steps are uncorrelated, surface topography becomes independent of step retreat rate and D is equal to 1.5. Under these conditions, measures of surface topography are not independent and any single topography parameter contains all of the available mechanistic information about the surface. Our results also indicate that root-mean-square roughness cannot be used to reliably characterize the surface topography of fractal surfaces because it is an inherently noisy parameter for such surfaces with the scale of the noise being independent of length scale.

Finger vein identification using fuzzy-based k-nearest centroid neighbor classifier

NASA Astrophysics Data System (ADS)

Rosdi, Bakhtiar Affendi; Jaafar, Haryati; Ramli, Dzati Athiar

2015-02-01

In this paper, a new approach for personal identification using finger vein image is presented. Finger vein is an emerging type of biometrics that attracts attention of researchers in biometrics area. As compared to other biometric traits such as face, fingerprint and iris, finger vein is more secured and hard to counterfeit since the features are inside the human body. So far, most of the researchers focus on how to extract robust features from the captured vein images. Not much research was conducted on the classification of the extracted features. In this paper, a new classifier called fuzzy-based k-nearest centroid neighbor (FkNCN) is applied to classify the finger vein image. The proposed FkNCN employs a surrounding rule to obtain the k-nearest centroid neighbors based on the spatial distributions of the training images and their distance to the test image. Then, the fuzzy membership function is utilized to assign the test image to the class which is frequently represented by the k-nearest centroid neighbors. Experimental evaluation using our own database which was collected from 492 fingers shows that the proposed FkNCN has better performance than the k-nearest neighbor, k-nearest-centroid neighbor and fuzzy-based-k-nearest neighbor classifiers. This shows that the proposed classifier is able to identify the finger vein image effectively.

The role of orthography in the semantic activation of neighbors.

PubMed

Hino, Yasushi; Lupker, Stephen J; Taylor, Tamsen E

2012-09-01

There is now considerable evidence that a letter string can activate semantic information appropriate to its orthographic neighbors (e.g., Forster & Hector's, 2002, TURPLE effect). This phenomenon is the focus of the present research. Using Japanese words, we examined whether semantic activation of neighbors is driven directly by orthographic similarity alone or whether there is also a role for phonological similarity. In Experiment 1, using a relatedness judgment task in which a Kanji word-Katakana word pair was presented on each trial, an inhibitory effect was observed when the initial Kanji word was related to an orthographic and phonological neighbor of the Katakana word target but not when the initial Kanji word was related to a phonological but not orthographic neighbor of the Katakana word target. This result suggests that phonology plays little, if any, role in the activation of neighbors' semantics when reading familiar words. In Experiment 2, the targets were transcribed into Hiragana, a script they are typically not written in, requiring readers to engage in phonological coding. In that experiment, inhibitory effects were observed in both conditions. This result indicates that phonologically mediated semantic activation of neighbors will emerge when phonological processing is necessary in order to understand a written word (e.g., when that word is transcribed into an unfamiliar script). PsycINFO Database Record (c) 2012 APA, all rights reserved.

Link prediction measures considering different neighbors’ effects and application in social networks

NASA Astrophysics Data System (ADS)

Luo, Peng; Wu, Chong; Li, Yongli

Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

Quantum Correlation in the XY Spin Model with Anisotropic Three-Site Interaction

NASA Astrophysics Data System (ADS)

Wang, Yao; Chai, Bing-Bing; Guo, Jin-Liang

2018-05-01

We investigate pairwise entanglement and quantum discord (QD) in the XY spin model with anisotropic three-site interaction at zero and finite temperatures. For both the nearest-neighbor spins and the next nearest-neighbor spins, special attention is paid to the dependence of entanglement and QD on the anisotropic parameter δ induced by the next nearest-neighbor spins. We show that the behavior of QD differs in many ways from entanglement under the influences of the anisotropic three-site interaction at finite temperatures. More important, comparing the effects of δ on the entanglement and QD, we find the anisotropic three-site interaction plays an important role in the quantum correlations at zero and finite temperatures. It is found that δ can strengthen the quantum correlation for both the nearest-neighbor spins and the next nearest-neighbor spins, especially for the nearest-neighbor spins at low temperature.

Ising lattices with +/-J second-nearest-neighbor interactions

NASA Astrophysics Data System (ADS)

Ramírez-Pastor, A. J.; Nieto, F.; Vogel, E. E.

1997-06-01

Second-nearest-neighbor interactions are added to the usual nearest-neighbor Ising Hamiltonian for square lattices in different ways. The starting point is a square lattice where half the nearest-neighbor interactions are ferromagnetic and the other half of the bonds are antiferromagnetic. Then, second-nearest-neighbor interactions can also be assigned randomly or in a variety of causal manners determined by the nearest-neighbor interactions. In the present paper we consider three causal and three random ways of assigning second-nearest-neighbor exchange interactions. Several ground-state properties are then calculated for each of these lattices:energy per bond ɛg, site correlation parameter pg, maximal magnetization μg, and fraction of unfrustrated bonds hg. A set of 500 samples is considered for each size N (number of spins) and array (way of distributing the N spins). The properties of the original lattices with only nearest-neighbor interactions are already known, which allows realizing the effect of the additional interactions. We also include cubic lattices to discuss the distinction between coordination number and dimensionality. Comparison with results for triangular and honeycomb lattices is done at specific points.

Robust Neighboring Optimal Guidance for the Advanced Launch System

NASA Technical Reports Server (NTRS)

Hull, David G.

1993-01-01

In recent years, optimization has become an engineering tool through the availability of numerous successful nonlinear programming codes. Optimal control problems are converted into parameter optimization (nonlinear programming) problems by assuming the control to be piecewise linear, making the unknowns the nodes or junction points of the linear control segments. Once the optimal piecewise linear control (suboptimal) control is known, a guidance law for operating near the suboptimal path is the neighboring optimal piecewise linear control (neighboring suboptimal control). Research conducted under this grant has been directed toward the investigation of neighboring suboptimal control as a guidance scheme for an advanced launch system.

Efficient Estimation of Mutual Information for Strongly Dependent Variables

DTIC Science & Technology

2015-05-11

the two possibilities: for a fixed dimension d and near- est neighbor parameter k, we find a constant ↵ k,d , such that if V̄ (i)/V (i) < ↵ k,d , then...also compare the results to several baseline estima- tors: KSG (Kraskov et al., 2004), generalized near- est neighbor graph (GNN) (Pál et al., 2010...Amaury Lendasse, and Francesco Corona. A boundary corrected expansion of the moments of near- est neighbor distributions. Random Struct. Algorithms

Orthographic neighborhood effects in recognition and recall tasks in a transparent orthography.

PubMed

Justi, Francis R R; Jaeger, Antonio

2017-04-01

The number of orthographic neighbors of a word influences its probability of being retrieved in recognition and free recall memory tests. Even though this phenomenon is well demonstrated for English words, it has yet to be demonstrated for languages with more predictable grapheme-phoneme mappings than English. To address this issue, 4 experiments were conducted to investigate effects of number of orthographic neighbors (N) and effects of frequency of occurrence of orthographic neighbors (NF) on memory retrieval of Brazilian Portuguese words. One hundred twenty-four Brazilian Portuguese speakers performed first a lexical-decision task (LDT) on words that were factorially manipulated according to N and NF, and intermixed with either nonpronounceable nonwords without orthographic neighbors (Experiments 1A and 2A), or with pronounceable nonwords with a large number of orthographic neighbors (Experiments 1B and 2B). The words were later used as probes on either recognition (Experiments 1A and 1B) or recall tests (Experiments 2A and 2B). Words with 1 orthographic neighbor were consistently better remembered than words with several orthographic neighbors in all recognition and recall tests. Notably, whereas in Experiment 1A higher false alarm rates were yielded for words with several rather than 1 orthographic neighbor, in Experiment 1B higher false alarm rates were yielded for words with 1 rather than several orthographic neighbors. Effects of NF, on the other hand, were not consistent among memory tasks. The effects of N on the recognition and recall tests conducted here are interpreted in light of dual process models of recognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

Seismic databases of The Caucasus

NASA Astrophysics Data System (ADS)

Gunia, I.; Sokhadze, G.; Mikava, D.; Tvaradze, N.; Godoladze, T.

2012-12-01

The Caucasus is one of the active segments of the Alpine-Himalayan collision belt. The region needs continues seismic monitoring systems for better understanding of tectonic processes going in the region. Seismic Monitoring Center of Georgia (Ilia State University) is operating the digital seismic network of the country and is also collecting and exchanging data with neighboring countries. The main focus of our study was to create seismic database which is well organized, easily reachable and is convenient for scientists to use. The seismological database includes the information about more than 100 000 earthquakes from the whole Caucasus. We have to mention that it includes data from analog and digital seismic networks. The first analog seismic station in Georgia was installed in 1899 in the Caucasus in Tbilisi city. The number of analog seismic stations was increasing during next decades and in 1980s about 100 analog stations were operated all over the region. From 1992 due to political and economical situation the number of stations has been decreased and in 2002 just two analog equipments was operated. New digital seismic network was developed in Georgia since 2003. The number of digital seismic stations was increasing and in current days there are more than 25 digital stations operating in the country. The database includes the detailed information about all equipments installed on seismic stations. Database is available online. That will make convenient interface for seismic data exchange data between Caucasus neighboring countries. It also makes easier both the seismic data processing and transferring them to the database and decreases the operator's mistakes during the routine work. The database was created using the followings: php, MySql, Javascript, Ajax, GMT, Gmap, Hypoinverse.

Extending GIS Technology to Study Karst Features of Southeastern Minnesota

NASA Astrophysics Data System (ADS)

Gao, Y.; Tipping, R. G.; Alexander, E. C.; Alexander, S. C.

2001-12-01

This paper summarizes ongoing research on karst feature distribution of southeastern Minnesota. The main goals of this interdisciplinary research are: 1) to look for large-scale patterns in the rate and distribution of sinkhole development; 2) to conduct statistical tests of hypotheses about the formation of sinkholes; 3) to create management tools for land-use managers and planners; and 4) to deliver geomorphic and hydrogeologic criteria for making scientifically valid land-use policies and ethical decisions in karst areas of southeastern Minnesota. Existing county and sub-county karst feature datasets of southeastern Minnesota have been assembled into a large GIS-based database capable of analyzing the entire data set. The central database management system (DBMS) is a relational GIS-based system interacting with three modules: GIS, statistical and hydrogeologic modules. ArcInfo and ArcView were used to generate a series of 2D and 3D maps depicting karst feature distributions in southeastern Minnesota. IRIS ExplorerTM was used to produce satisfying 3D maps and animations using data exported from GIS-based database. Nearest-neighbor analysis has been used to test sinkhole distributions in different topographic and geologic settings. All current nearest-neighbor analyses testify that sinkholes in southeastern Minnesota are not evenly distributed in this area (i.e., they tend to be clustered). More detailed statistical methods such as cluster analysis, histograms, probability estimation, correlation and regression have been used to study the spatial distributions of some mapped karst features of southeastern Minnesota. A sinkhole probability map for Goodhue County has been constructed based on sinkhole distribution, bedrock geology, depth to bedrock, GIS buffer analysis and nearest-neighbor analysis. A series of karst features for Winona County including sinkholes, springs, seeps, stream sinks and outcrop has been mapped and entered into the Karst Feature Database of Southeastern Minnesota. The Karst Feature Database of Winona County is being expanded to include all the mapped karst features of southeastern Minnesota. Air photos from 1930s to 1990s of Spring Valley Cavern Area in Fillmore County were scanned and geo-referenced into our GIS system. This technology has been proved to be very useful to identify sinkholes and study the rate of sinkhole development.

Enhancement and inhibition of light tunneling mediated by resonant mode conversion.

PubMed

Kartashov, Yaroslav V; Vysloukh, Victor A; Torner, Lluis

2014-02-15

We show that the rate at which light tunnels between neighboring multimode waveguides can be drastically increased or reduced by the presence of small longitudinal periodic modulations of the waveguide properties that stimulate resonant conversion between the eigenmodes of each waveguide. Such a conversion, available only in multimode guiding structures, leads to periodic power transfer into higher-order modes, whose tails may considerably overlap with neighboring waveguides. As a result, the effective coupling constant for neighboring waveguides may change by several orders of magnitude upon small variations in the longitudinal modulation parameters.

Estimating forest attribute parameters for small areas using nearest neighbors techniques

Treesearch

Ronald E. McRoberts

2012-01-01

Nearest neighbors techniques have become extremely popular, particularly for use with forest inventory data. With these techniques, a population unit prediction is calculated as a linear combination of observations for a selected number of population units in a sample that are most similar, or nearest, in a space of ancillary variables to the population unit requiring...

Digital auscultation analysis for heart murmur detection.

PubMed

Delgado-Trejos, Edilson; Quiceno-Manrique, A F; Godino-Llorente, J I; Blanco-Velasco, M; Castellanos-Dominguez, G

2009-02-01

This work presents a comparison of different approaches for the detection of murmurs from phonocardiographic signals. Taking into account the variability of the phonocardiographic signals induced by valve disorders, three families of features were analyzed: (a) time-varying & time-frequency features; (b) perceptual; and (c) fractal features. With the aim of improving the performance of the system, the accuracy of the system was tested using several combinations of the aforementioned families of parameters. In the second stage, the main components extracted from each family were combined together with the goal of improving the accuracy of the system. The contribution of each family of features extracted was evaluated by means of a simple k-nearest neighbors classifier, showing that fractal features provide the best accuracy (97.17%), followed by time-varying & time-frequency (95.28%), and perceptual features (88.7%). However, an accuracy around 94% can be reached just by using the two main features of the fractal family; therefore, considering the difficulties related to the automatic intrabeat segmentation needed for spectral and perceptual features, this scheme becomes an interesting alternative. The conclusion is that fractal type features were the most robust family of parameters (in the sense of accuracy vs. computational load) for the automatic detection of murmurs. This work was carried out using a database that contains 164 phonocardiographic recordings (81 normal and 83 records with murmurs). The database was segmented to extract 360 representative individual beats (180 per class).

The Amordad database engine for metagenomics.

PubMed

Behnam, Ehsan; Smith, Andrew D

2014-10-15

Several technical challenges in metagenomic data analysis, including assembling metagenomic sequence data or identifying operational taxonomic units, are both significant and well known. These forms of analysis are increasingly cited as conceptually flawed, given the extreme variation within traditionally defined species and rampant horizontal gene transfer. Furthermore, computational requirements of such analysis have hindered content-based organization of metagenomic data at large scale. In this article, we introduce the Amordad database engine for alignment-free, content-based indexing of metagenomic datasets. Amordad places the metagenome comparison problem in a geometric context, and uses an indexing strategy that combines random hashing with a regular nearest neighbor graph. This framework allows refinement of the database over time by continual application of random hash functions, with the effect of each hash function encoded in the nearest neighbor graph. This eliminates the need to explicitly maintain the hash functions in order for query efficiency to benefit from the accumulated randomness. Results on real and simulated data show that Amordad can support logarithmic query time for identifying similar metagenomes even as the database size reaches into the millions. Source code, licensed under the GNU general public license (version 3) is freely available for download from http://smithlabresearch.org/amordad andrewds@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A multilevel-skin neighbor list algorithm for molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Zhao, Mingcan; Hou, Chaofeng; Ge, Wei

2018-01-01

Searching of the interaction pairs and organization of the interaction processes are important steps in molecular dynamics (MD) algorithms and are critical to the overall efficiency of the simulation. Neighbor lists are widely used for these steps, where thicker skin can reduce the frequency of list updating but is discounted by more computation in distance check for the particle pairs. In this paper, we propose a new neighbor-list-based algorithm with a precisely designed multilevel skin which can reduce unnecessary computation on inter-particle distances. The performance advantages over traditional methods are then analyzed against the main simulation parameters on Intel CPUs and MICs (many integrated cores), and are clearly demonstrated. The algorithm can be generalized for various discrete simulations using neighbor lists.

Local neighborhood transition probability estimation and its use in contextual classification

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of incorporating spatial or contextual information into classifications is considered. A simple model that describes the spatial dependencies between the neighboring pixels with a single parameter, Theta, is presented. Expressions are derived for updating the posteriori probabilities of the states of nature of the pattern under consideration using information from the neighboring patterns, both for spatially uniform context and for Markov dependencies in terms of Theta. Techniques for obtaining the optimal value of the parameter Theta as a maximum likelihood estimate from the local neighborhood of the pattern under consideration are developed.

Exploring neighborhoods in the metagenome universe.

PubMed

Aßhauer, Kathrin P; Klingenberg, Heiner; Lingner, Thomas; Meinicke, Peter

2014-07-14

The variety of metagenomes in current databases provides a rapidly growing source of information for comparative studies. However, the quantity and quality of supplementary metadata is still lagging behind. It is therefore important to be able to identify related metagenomes by means of the available sequence data alone. We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. In a broad comparison of different profiling methods we found that vector-based distance measures are well-suitable for the detection of metagenomic neighbors. Our evaluation on more than 1700 publicly available metagenomes indicates that for a query metagenome from a particular habitat on average nine out of ten nearest neighbors represent the same habitat category independent of the utilized profiling method or distance measure. While for well-defined labels a neighborhood accuracy of 100% can be achieved, in general the neighbor detection is severely affected by a natural overlap of manually annotated categories. In addition, we present results of a novel visualization method that is able to reflect the similarity of metagenomes in a 2D scatter plot. The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. Our study suggests that for inspection of metagenome neighborhoods the profiling methods and distance measures can be chosen to provide a convenient interpretation of results in terms of the underlying features. Furthermore, supplementary metadata of metagenome samples in the future needs to comply with readily available ontologies for fine-grained and standardized annotation. To make profile-based k-nearest-neighbor search and the 2D-visualization of the metagenome universe available to the research community, we included the proposed methods in our CoMet-Universe server for comparative metagenome analysis.

Exploring Neighborhoods in the Metagenome Universe

PubMed Central

Aßhauer, Kathrin P.; Klingenberg, Heiner; Lingner, Thomas; Meinicke, Peter

2014-01-01

The variety of metagenomes in current databases provides a rapidly growing source of information for comparative studies. However, the quantity and quality of supplementary metadata is still lagging behind. It is therefore important to be able to identify related metagenomes by means of the available sequence data alone. We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. In a broad comparison of different profiling methods we found that vector-based distance measures are well-suitable for the detection of metagenomic neighbors. Our evaluation on more than 1700 publicly available metagenomes indicates that for a query metagenome from a particular habitat on average nine out of ten nearest neighbors represent the same habitat category independent of the utilized profiling method or distance measure. While for well-defined labels a neighborhood accuracy of 100% can be achieved, in general the neighbor detection is severely affected by a natural overlap of manually annotated categories. In addition, we present results of a novel visualization method that is able to reflect the similarity of metagenomes in a 2D scatter plot. The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. Our study suggests that for inspection of metagenome neighborhoods the profiling methods and distance measures can be chosen to provide a convenient interpretation of results in terms of the underlying features. Furthermore, supplementary metadata of metagenome samples in the future needs to comply with readily available ontologies for fine-grained and standardized annotation. To make profile-based k-nearest-neighbor search and the 2D-visualization of the metagenome universe available to the research community, we included the proposed methods in our CoMet-Universe server for comparative metagenome analysis. PMID:25026170

GIS-BASED RISK ASSESSMENT OF PESTICIDE DRIFT CASE STUDY: FRESNO COUNTY, CALIFORNIA

EPA Science Inventory

The report describes the potential risk of herbicide drift and accidentally damaging neighboring crops or surrounding native vegetation. This study is the first to use the California Pesticide Use Reporting database within a mapping framework (known as a Geographic Information S...

Partner switching promotes cooperation among myopic agents on a geographical plane

NASA Astrophysics Data System (ADS)

Li, Yixiao; Min, Yong; Zhu, Xiaodong; Cao, Jie

2013-02-01

We study the coupling dynamics between the evolution of cooperation and the evolution of partnership network on a geographical plane. While agents play networked prisoner’s dilemma games, they can dynamically adjust their partnerships based on local information about reputation. We incorporate geographical features into the process of the agent’s partner switching and investigate the corresponding effects. At each time step of the coevolution, a random agent can either update his strategy by imitation or adjust his partnership by switching from the lowest reputation partner to the highest reputation one among his neighbors. We differentiate two types of neighbors: geographical neighbors (i.e., the set of agents who are close to the focal agent in terms of geographical distance) and connectivity neighbors (i.e., the set of agents who are close to the focal agent in the partnership network in terms of geodesic distance). We find that switching to either geographical neighbors or connectivity neighbors enhances cooperation greatly in a wide parameter range. Cooperation can be favored in a much stricter condition when agents switch to connectivity neighbors more frequently. However, an increasing tendency of reconnecting to geographical neighbors shortens the geographical distance between a pair of partners on average. When agents consider the cost of geographical distance in adjusting the partnership, they are prone to reconnect to geographical neighbors.

Using genetic algorithms to optimize k-Nearest Neighbors configurations for use with airborne laser scanning data

Treesearch

Ronald E. McRoberts; Grant M. Domke; Qi Chen; Erik Næsset; Terje Gobakken

2016-01-01

The relatively small sampling intensities used by national forest inventories are often insufficient to produce the desired precision for estimates of population parameters unless the estimation process is augmented with auxiliary information, usually in the form of remotely sensed data. The k-Nearest Neighbors (k-NN) technique is a non-parametric,multivariate approach...

Nearest-neighbor thermodynamics of deoxyinosine pairs in DNA duplexes

PubMed Central

Watkins, Norman E.; SantaLucia, John

2005-01-01

Nearest-neighbor thermodynamic parameters of the ‘universal pairing base’ deoxyinosine were determined for the pairs I·C, I·A, I·T, I·G and I·I adjacent to G·C and A·T pairs. Ultraviolet absorbance melting curves were measured and non-linear regression performed on 84 oligonucleotide duplexes with 9 or 12 bp lengths. These data were combined with data for 13 inosine containing duplexes from the literature. Multiple linear regression was used to solve for the 32 nearest-neighbor unknowns. The parameters predict the Tm for all sequences within 1.2°C on average. The general trend in decreasing stability is I·C > I·A > I·T ≈ I· G > I·I. The stability trend for the base pair 5′ of the I·X pair is G·C > C·G > A·T > T·A. The stability trend for the base pair 3′ of I·X is the same. These trends indicate a complex interplay between H-bonding, nearest-neighbor stacking, and mismatch geometry. A survey of 14 tandem inosine pairs and 8 tandem self-complementary inosine pairs is also provided. These results may be used in the design of degenerate PCR primers and for degenerate microarray probes. PMID:16264087

Computer Simulation of Energy Parameters and Magnetic Effects in Fe-Si-C Ternary Alloys

NASA Astrophysics Data System (ADS)

Ridnyi, Ya. M.; Mirzoev, A. A.; Mirzaev, D. A.

2018-06-01

The paper presents ab initio simulation with the WIEN2k software package of the equilibrium structure and properties of silicon and carbon atoms dissolved in iron with the body-centered cubic crystal system of the lattice. Silicon and carbon atoms manifest a repulsive interaction in the first two nearest neighbors, in the second neighbor the repulsion being stronger than in the first. In the third and next-nearest neighbors a very weak repulsive interaction occurs and tends to zero with increasing distance between atoms. Silicon and carbon dissolution reduces the magnetic moment of iron atoms.

Lattice-dynamical model for the filled skutterudite LaFe4Sb12: Harmonic and anharmonic couplings

NASA Astrophysics Data System (ADS)

Feldman, J. L.; Singh, D. J.; Bernstein, N.

2014-06-01

The filled skutterudite LaFe4Sb12 shows greatly reduced thermal conductivity compared to that of the related unfilled compound CoSb3, although the microscopic reasons for this are unclear. We calculate harmonic and anharmonic force constants for the interaction of the La filler atom with the framework atoms. We find that force constants show a general trend of decaying rapidly with distance and are very small for the interaction of the La with its next-nearest-neighbor Sb and nearest-neighbor La. However, a few rather long-range interactions, such as with the next-nearest-neighbor La and with the third neighbor Sb, are surprisingly strong, although still small. We test the central-force approximation and find significant deviations from it. Using our force constants we calculate a bare La mode Gruneisen parameter and find a value of 3-4, substantially higher than values associated with cage atom anharmonicity, i.e., a value of about 1 for CoSb3 but much smaller than a previous estimate [Bernstein et al., Phys. Rev. B 81, 134301 (2010), 10.1103/PhysRevB.81.134301]. This latter difference is primarily due to the previously used overestimate of the La-Fe cubic force constants. We also find a substantial negative contribution to this bare La Gruneisen parameter from the aforementioned third-neighbor La-Sb interaction. Our results underscore the need for rather long-range interactions in describing the role of anharmonicity on the dynamics in this material.

Predictions of nuclear charge radii

NASA Astrophysics Data System (ADS)

Bao, M.; Lu, Y.; Zhao, Y. M.; Arima, A.

2016-12-01

The nuclear charge radius is a fundamental property of an atomic nucleus. In this article we study the predictive power of empirical relations for experimental nuclear charge radii of neighboring nuclei and predict the unknown charge radii of 1085 nuclei based on the experimental CR2013 database within an uncertainty of 0.03 fm.

Creating peer groups for assessing and comparing nursing home performance.

PubMed

Byrne, Margaret M; Daw, Christina; Pietz, Ken; Reis, Brian; Petersen, Laura A

2013-11-01

Publicly reported performance data for hospitals and nursing homes are becoming ubiquitous. For such comparisons to be fair, facilities must be compared with their peers. To adapt a previously published methodology for developing hospital peer groupings so that it is applicable to nursing homes and to explore the characteristics of "nearest-neighbor" peer groupings. Analysis of Department of Veterans Affairs administrative databases and nursing home facility characteristics. The nearest-neighbor methodology for developing peer groupings involves calculating the Euclidean distance between facilities based on facility characteristics. We describe our steps in selection of facility characteristics, describe the characteristics of nearest-neighbor peer groups, and compare them with peer groups derived through classical cluster analysis. The facility characteristics most pertinent to nursing home groupings were found to be different from those that were most relevant for hospitals. Unlike classical cluster groups, nearest neighbor groups are not mutually exclusive, and the nearest-neighbor methodology resulted in nursing home peer groupings that were substantially less diffuse than nursing home peer groups created using traditional cluster analysis. It is essential that healthcare policy makers and administrators have a means of fairly grouping facilities for the purposes of quality, cost, or efficiency comparisons. In this research, we show that a previously published methodology can be successfully applied to a nursing home setting. The same approach could be applied in other clinical settings such as primary care.

A systematic molecular dynamics study of nearest-neighbor effects on base pair and base pair step conformations and fluctuations in B-DNA

PubMed Central

Lavery, Richard; Zakrzewska, Krystyna; Beveridge, David; Bishop, Thomas C.; Case, David A.; Cheatham, Thomas; Dixit, Surjit; Jayaram, B.; Lankas, Filip; Laughton, Charles; Maddocks, John H.; Michon, Alexis; Osman, Roman; Orozco, Modesto; Perez, Alberto; Singh, Tanya; Spackova, Nada; Sponer, Jiri

2010-01-01

It is well recognized that base sequence exerts a significant influence on the properties of DNA and plays a significant role in protein–DNA interactions vital for cellular processes. Understanding and predicting base sequence effects requires an extensive structural and dynamic dataset which is currently unavailable from experiment. A consortium of laboratories was consequently formed to obtain this information using molecular simulations. This article describes results providing information not only on all 10 unique base pair steps, but also on all possible nearest-neighbor effects on these steps. These results are derived from simulations of 50–100 ns on 39 different DNA oligomers in explicit solvent and using a physiological salt concentration. We demonstrate that the simulations are converged in terms of helical and backbone parameters. The results show that nearest-neighbor effects on base pair steps are very significant, implying that dinucleotide models are insufficient for predicting sequence-dependent behavior. Flanking base sequences can notably lead to base pair step parameters in dynamic equilibrium between two conformational sub-states. Although this study only provides limited data on next-nearest-neighbor effects, we suggest that such effects should be analyzed before attempting to predict the sequence-dependent behavior of DNA. PMID:19850719

Ground-state ordering of the J1-J2 model on the simple cubic and body-centered cubic lattices

NASA Astrophysics Data System (ADS)

Farnell, D. J. J.; Götze, O.; Richter, J.

2016-06-01

The J1-J2 Heisenberg model is a "canonical" model in the field of quantum magnetism in order to study the interplay between frustration and quantum fluctuations as well as quantum phase transitions driven by frustration. Here we apply the coupled cluster method (CCM) to study the spin-half J1-J2 model with antiferromagnetic nearest-neighbor bonds J1>0 and next-nearest-neighbor bonds J2>0 for the simple cubic (sc) and body-centered cubic (bcc) lattices. In particular, we wish to study the ground-state ordering of these systems as a function of the frustration parameter p =z2J2/z1J1 , where z1 (z2) is the number of nearest (next-nearest) neighbors. We wish to determine the positions of the phase transitions using the CCM and we aim to resolve the nature of the phase transition points. We consider the ground-state energy, order parameters, spin-spin correlation functions, as well as the spin stiffness in order to determine the ground-state phase diagrams of these models. We find a direct first-order phase transition at a value of p =0.528 from a state of nearest-neighbor Néel order to next-nearest-neighbor Néel order for the bcc lattice. For the sc lattice the situation is more subtle. CCM results for the energy, the order parameter, the spin-spin correlation functions, and the spin stiffness indicate that there is no direct first-order transition between ground-state phases with magnetic long-range order, rather it is more likely that two phases with antiferromagnetic long range are separated by a narrow region of a spin-liquid-like quantum phase around p =0.55 . Thus the strong frustration present in the J1-J2 Heisenberg model on the sc lattice may open a window for an unconventional quantum ground state in this three-dimensional spin model.

Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

PubMed Central

Brković, Milenko; Simić, Mirjana

2014-01-01

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443

Application of Large-Scale Database-Based Online Modeling to Plant State Long-Term Estimation

NASA Astrophysics Data System (ADS)

Ogawa, Masatoshi; Ogai, Harutoshi

Recently, attention has been drawn to the local modeling techniques of a new idea called “Just-In-Time (JIT) modeling”. To apply “JIT modeling” to a large amount of database online, “Large-scale database-based Online Modeling (LOM)” has been proposed. LOM is a technique that makes the retrieval of neighboring data more efficient by using both “stepwise selection” and quantization. In order to predict the long-term state of the plant without using future data of manipulated variables, an Extended Sequential Prediction method of LOM (ESP-LOM) has been proposed. In this paper, the LOM and the ESP-LOM are introduced.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Evolution of Cooperation in Continuous Prisoner's Dilemma Games on Barabasi—Albert Networks with Degree-Dependent Guilt Mechanism

NASA Astrophysics Data System (ADS)

Wang, Xian-Jia; Quan, Ji; Liu, Wei-Bing

2012-05-01

This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi—Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms.

Isolated Early-type Galaxies in the 2dFGRS

NASA Astrophysics Data System (ADS)

Fuse, Christopher R.; Lamir, C.

2014-01-01

Isolated galaxies are systems that have experienced limited external perturbations, thus the properties of these galaxies are largely due to internal processes. The features of isolated early-type galaxies (IEGs) provide a baseline from which to compare early-type systems residing in higher-density environments. We use the Two-Degree Field Galaxy Redshift Survey (2dFGRS) and the NASA Extragalactic Database (NED) to identify IEGs in the nearby universe. Search criteria in the 2dFGRS were chosen to insure that the IEGs have remained separated from neighboring galaxies for the majority of their lifetimes. Isolated galaxies are chosen utilizing a minimum projected physical separation of 1 Mpc from any neighboring non-dwarf galaxy brighter than Mb = -16.5 mags. A minimum redshift separation of 350 km/s between a candidate galaxy and a neighboring was imposed to further insure the candidate’s isolation. Early results of the search for isolated early-type galaxies in the southern sky are presented.

Neighboring extremals of dynamic optimization problems with path equality constraints

NASA Technical Reports Server (NTRS)

Lee, A. Y.

1988-01-01

Neighboring extremals of dynamic optimization problems with path equality constraints and with an unknown parameter vector are considered in this paper. With some simplifications, the problem is reduced to solving a linear, time-varying two-point boundary-value problem with integral path equality constraints. A modified backward sweep method is used to solve this problem. Two example problems are solved to illustrate the validity and usefulness of the solution technique.

Solitonlike pulses along a modified Noguchi nonlinear electrical network with second-neighbor interactions: Analytical studies

NASA Astrophysics Data System (ADS)

Kengne, E.; Liu, W. M.

2018-05-01

A modified lossless nonlinear Noguchi transmission network with second-neighbor interactions is considered. In the semidiscrete limit, we apply the reductive perturbation method and show that the dynamics of modulated waves propagating through the network are governed by an NLS equation with linear external potential. Classes of exact solitonic solutions of this network equation are derived, proving possible transmission of both bright and dark solitonlike pulses through the network. The effects of both the coupling second-neighbor parameter L3 and the strength λ of the linear potential on the dynamics of modulated waves through the network are investigated. One of the main results of our work is that with the introduction of the second neighbors in the network, two solitary signals, either two bright solitary signals or one bright and one dark solitary signal, may simultaneously propagate at the same frequency through the network.

Dynamical phases in a one-dimensional chain of heterospecies Rydberg atoms with next-nearest-neighbor interactions

NASA Astrophysics Data System (ADS)

Qian, Jing; Zhang, Lu; Zhai, Jingjing; Zhang, Weiping

2015-12-01

We theoretically investigate the dynamical phase diagram of a one-dimensional chain of laser-excited two-species Rydberg atoms. The existence of a variety of unique dynamical phases in the experimentally achievable parameter region is predicted under the mean-field approximation, and the change in those phases when the effect of the next-nearest-neighbor interaction is included is further discussed. In particular, we find that the com-petition of the strong Rydberg-Rydberg interactions and the optical excitation imbalance can lead to the presence of complex multiple chaotic phases, which are highly sensitive to the initial Rydberg-state population and the strength of the next-nearest-neighbor interactions.

G-Hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases.

PubMed

Wang, Xiaohong; Smalter, Aaron; Huan, Jun; Lushington, Gerald H

2009-01-01

Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and similarity search. With the fast accumulation of graph databases, similarity search in graph databases has emerged as an important research topic. Graph similarity search has applications in a wide range of domains including cheminformatics, bioinformatics, sensor network management, social network management, and XML documents, among others.Most of the current graph indexing methods focus on subgraph query processing, i.e. determining the set of database graphs that contains the query graph and hence do not directly support similarity search. In data mining and machine learning, various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models for supervised learning, graph kernel functions have (i) high computational complexity and (ii) non-trivial difficulty to be indexed in a graph database.Our objective is to bridge graph kernel function and similarity search in graph databases by proposing (i) a novel kernel-based similarity measurement and (ii) an efficient indexing structure for graph data management. Our method of similarity measurement builds upon local features extracted from each node and their neighboring nodes in graphs. A hash table is utilized to support efficient storage and fast search of the extracted local features. Using the hash table, a graph kernel function is defined to capture the intrinsic similarity of graphs and for fast similarity query processing. We have implemented our method, which we have named G-hash, and have demonstrated its utility on large chemical graph databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Most importantly, the new similarity measurement and the index structure is scalable to large database with smaller indexing size, faster indexing construction time, and faster query processing time as compared to state-of-the-art indexing methods such as C-tree, gIndex, and GraphGrep.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Progressive sparse representation-based classification using local discrete cosine transform evaluation for image recognition

NASA Astrophysics Data System (ADS)

Song, Xiaoning; Feng, Zhen-Hua; Hu, Guosheng; Yang, Xibei; Yang, Jingyu; Qi, Yunsong

2015-09-01

This paper proposes a progressive sparse representation-based classification algorithm using local discrete cosine transform (DCT) evaluation to perform face recognition. Specifically, the sum of the contributions of all training samples of each subject is first taken as the contribution of this subject, then the redundant subject with the smallest contribution to the test sample is iteratively eliminated. Second, the progressive method aims at representing the test sample as a linear combination of all the remaining training samples, by which the representation capability of each training sample is exploited to determine the optimal "nearest neighbors" for the test sample. Third, the transformed DCT evaluation is constructed to measure the similarity between the test sample and each local training sample using cosine distance metrics in the DCT domain. The final goal of the proposed method is to determine an optimal weighted sum of nearest neighbors that are obtained under the local correlative degree evaluation, which is approximately equal to the test sample, and we can use this weighted linear combination to perform robust classification. Experimental results conducted on the ORL database of faces (created by the Olivetti Research Laboratory in Cambridge), the FERET face database (managed by the Defense Advanced Research Projects Agency and the National Institute of Standards and Technology), AR face database (created by Aleix Martinez and Robert Benavente in the Computer Vision Center at U.A.B), and USPS handwritten digit database (gathered at the Center of Excellence in Document Analysis and Recognition at SUNY Buffalo) demonstrate the effectiveness of the proposed method.

The practical evaluation of DNA barcode efficacy.

PubMed

Spouge, John L; Mariño-Ramírez, Leonardo

2012-01-01

This chapter describes a workflow for measuring the efficacy of a barcode in identifying species. First, assemble individual sequence databases corresponding to each barcode marker. A controlled collection of taxonomic data is preferable to GenBank data, because GenBank data can be problematic, particularly when comparing barcodes based on more than one marker. To ensure proper controls when evaluating species identification, specimens not having a sequence in every marker database should be discarded. Second, select a computer algorithm for assigning species to barcode sequences. No algorithm has yet improved notably on assigning a specimen to the species of its nearest neighbor within a barcode database. Because global sequence alignments (e.g., with the Needleman-Wunsch algorithm, or some related algorithm) examine entire barcode sequences, they generally produce better species assignments than local sequence alignments (e.g., with BLAST). No neighboring method (e.g., global sequence similarity, global sequence distance, or evolutionary distance based on a global alignment) has yet shown a notable superiority in identifying species. Finally, "the probability of correct identification" (PCI) provides an appropriate measurement of barcode efficacy. The overall PCI for a data set is the average of the species PCIs, taken over all species in the data set. This chapter states explicitly how to calculate PCI, how to estimate its statistical sampling error, and how to use data on PCR failure to set limits on how much improvements in PCR technology can improve species identification.

McIntosh active-region class similarities and suggestions for mergers

NASA Technical Reports Server (NTRS)

Bornmann, P. L.; Kalmbach, D.; Kulhanek, D.

1994-01-01

McIntosh active-region classifications reported during a five-year period were examined to determine similarities among the classes. Two methods were used extensively to determine these similarities. The number of transitions among classes were used to determine the most frequent transitions out of each class, and the alternative classes reported for the same region by different sites were used to establish which classes were neighboring classes. These transition frequencies and neighboring classes were used to identify classes that could be eliminated or merged with other classes. Class similarities were used to investigate the relative importance of several pairs of decisions that occur within a single McIntosh parameter. In particular, the redundancy of parameters in some classes was examined, and the class similarities were used to identify which of these parameters could be eliminated. Infrequently reported classes were also considered, and suggestions for mergers were made when similarities between classes could be identified.

Virus Database and Online Inquiry System Based on Natural Vectors.

PubMed

Dong, Rui; Zheng, Hui; Tian, Kun; Yau, Shek-Chung; Mao, Weiguang; Yu, Wenping; Yin, Changchuan; Yu, Chenglong; He, Rong Lucy; Yang, Jie; Yau, Stephen St

2017-01-01

We construct a virus database called VirusDB (http://yaulab.math.tsinghua.edu.cn/VirusDB/) and an online inquiry system to serve people who are interested in viral classification and prediction. The database stores all viral genomes, their corresponding natural vectors, and the classification information of the single/multiple-segmented viral reference sequences downloaded from National Center for Biotechnology Information. The online inquiry system serves the purpose of computing natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for viral classification and prediction, and back-end processes for automatic and manual updating of database content to synchronize with GenBank. Submitted genomes data in FASTA format will be carried out and the prediction results with 5 closest neighbors and their classifications will be returned by email. Considering the one-to-one correspondence between sequence and natural vector, time efficiency, and high accuracy, natural vector is a significant advance compared with alignment methods, which makes VirusDB a useful database in further research.

An Improvement To The k-Nearest Neighbor Classifier For ECG Database

NASA Astrophysics Data System (ADS)

Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

2018-03-01

The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

PubMed

Hussain, Lal

2018-06-01

Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the brain. The research reveals that brain activity is monitored through electroencephalogram (EEG) of patients suffered from seizure to detect the epileptic seizure. The performance of EEG detection based epilepsy require feature extracting strategies. In this research, we have extracted varying features extracting strategies based on time and frequency domain characteristics, nonlinear, wavelet based entropy and few statistical features. A deeper study was undertaken using novel machine learning classifiers by considering multiple factors. The support vector machine kernels are evaluated based on multiclass kernel and box constraint level. Likewise, for K-nearest neighbors (KNN), we computed the different distance metrics, Neighbor weights and Neighbors. Similarly, the decision trees we tuned the paramours based on maximum splits and split criteria and ensemble classifiers are evaluated based on different ensemble methods and learning rate. For training/testing tenfold Cross validation was employed and performance was evaluated in form of TPR, NPR, PPV, accuracy and AUC. In this research, a deeper analysis approach was performed using diverse features extracting strategies using robust machine learning classifiers with more advanced optimal options. Support Vector Machine linear kernel and KNN with City block distance metric give the overall highest accuracy of 99.5% which was higher than using the default parameters for these classifiers. Moreover, highest separation (AUC = 0.9991, 0.9990) were obtained at different kernel scales using SVM. Additionally, the K-nearest neighbors with inverse squared distance weight give higher performance at different Neighbors. Moreover, to distinguish the postictal heart rate oscillations from epileptic ictal subjects, and highest performance of 100% was obtained using different machine learning classifiers.

Procura-PALavras (P-PAL): A Web-based interface for a new European Portuguese lexical database.

PubMed

Soares, Ana Paula; Iriarte, Álvaro; de Almeida, José João; Simões, Alberto; Costa, Ana; Machado, João; França, Patrícia; Comesaña, Montserrat; Rauber, Andreia; Rato, Anabela; Perea, Manuel

2018-05-31

In this article, we present Procura-PALavras (P-PAL), a Web-based interface for a new European Portuguese (EP) lexical database. Based on a contemporary printed corpus of over 227 million words, P-PAL provides a broad range of word attributes and statistics, including several measures of word frequency (e.g., raw counts, per-million word frequency, logarithmic Zipf scale), morpho-syntactic information (e.g., parts of speech [PoSs], grammatical gender and number, dominant PoS, and frequency and relative frequency of the dominant PoS), as well as several lexical and sublexical orthographic (e.g., number of letters; consonant-vowel orthographic structure; density and frequency of orthographic neighbors; orthographic Levenshtein distance; orthographic uniqueness point; orthographic syllabification; and trigram, bigram, and letter type and token frequencies), and phonological measures (e.g., pronunciation, number of phonemes, stress, density and frequency of phonological neighbors, transposed and phonographic neighbors, syllabification, and biphone and phone type and token frequencies) for ~53,000 lemmatized and ~208,000 nonlemmatized EP word forms. To obtain these metrics, researchers can choose between two word queries in the application: (i) analyze words previously selected for specific attributes and/or lexical and sublexical characteristics, or (ii) generate word lists that meet word requirements defined by the user in the menu of analyses. For the measures it provides and the flexibility it allows, P-PAL will be a key resource to support research in all cognitive areas that use EP verbal stimuli. P-PAL is freely available at http://p-pal.di.uminho.pt/tools .

Phase transition in the spin- 3 / 2 Blume-Emery-Griffiths model with antiferromagnetic second neighbor interactions

NASA Astrophysics Data System (ADS)

Yezli, M.; Bekhechi, S.; Hontinfinde, F.; EZ-Zahraouy, H.

2016-04-01

Two nonperturbative methods such as Monte-Carlo simulation (MC) and Transfer-Matrix Finite-Size-Scaling calculations (TMFSS) have been used to study the phase transition of the spin- 3 / 2 ​Blume-Emery-Griffiths model (BEG) with quadrupolar and antiferromagnetic next-nearest-neighbor exchange interactions. Ground state and finite temperature phase diagrams are obtained by means of these two methods. New degenerate phases are found and only second order phase transitions occur for all values of the parameter interactions. No sign of the intermediate phase is found from both methods. Critical exponents are also obtained from TMFSS calculations. Ising criticality and nonuniversal behaviors are observed depending on the strength of the second neighbor interaction.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Synergistic effects in threshold models on networks.

PubMed

Juul, Jonas S; Porter, Mason A

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can-depending on a parameter-either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Forensic DNA databases in Western Balkan region: retrospectives, perspectives, and initiatives

PubMed Central

Marjanović, Damir; Konjhodžić, Rijad; Butorac, Sara Sanela; Drobnič, Katja; Merkaš, Siniša; Lauc, Gordan; Primorac, Damir; Anđelinović, Šimun; Milosavljević, Mladen; Karan, Željko; Vidović, Stojko; Stojković, Oliver; Panić, Bojana; Vučetić Dragović, Anđelka; Kovačević, Sandra; Jakovski, Zlatko; Asplen, Chris; Primorac, Dragan

2011-01-01

The European Network of Forensic Science Institutes (ENFSI) recommended the establishment of forensic DNA databases and specific implementation and management legislations for all EU/ENFSI members. Therefore, forensic institutions from Bosnia and Herzegovina, Serbia, Montenegro, and Macedonia launched a wide set of activities to support these recommendations. To assess the current state, a regional expert team completed detailed screening and investigation of the existing forensic DNA data repositories and associated legislation in these countries. The scope also included relevant concurrent projects and a wide spectrum of different activities in relation to forensics DNA use. The state of forensic DNA analysis was also determined in the neighboring Slovenia and Croatia, which already have functional national DNA databases. There is a need for a ‘regional supplement’ to the current documentation and standards pertaining to forensic application of DNA databases, which should include regional-specific preliminary aims and recommendations. PMID:21674821

Forensic DNA databases in Western Balkan region: retrospectives, perspectives, and initiatives.

PubMed

Marjanović, Damir; Konjhodzić, Rijad; Butorac, Sara Sanela; Drobnic, Katja; Merkas, Sinisa; Lauc, Gordan; Primorac, Damir; Andjelinović, Simun; Milosavljević, Mladen; Karan, Zeljko; Vidović, Stojko; Stojković, Oliver; Panić, Bojana; Vucetić Dragović, Andjelka; Kovacević, Sandra; Jakovski, Zlatko; Asplen, Chris; Primorac, Dragan

2011-06-01

The European Network of Forensic Science Institutes (ENFSI) recommended the establishment of forensic DNA databases and specific implementation and management legislations for all EU/ENFSI members. Therefore, forensic institutions from Bosnia and Herzegovina, Serbia, Montenegro, and Macedonia launched a wide set of activities to support these recommendations. To assess the current state, a regional expert team completed detailed screening and investigation of the existing forensic DNA data repositories and associated legislation in these countries. The scope also included relevant concurrent projects and a wide spectrum of different activities in relation to forensics DNA use. The state of forensic DNA analysis was also determined in the neighboring Slovenia and Croatia, which already have functional national DNA databases. There is a need for a 'regional supplement' to the current documentation and standards pertaining to forensic application of DNA databases, which should include regional-specific preliminary aims and recommendations.

A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and k-Nearest Neighbor Graph

PubMed Central

Pan, Yongke; Niu, Wenjia

2017-01-01

Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, to enhance the performance of SDA. Different from these relative works, the regularized graph construction is researched here, which is important in the graph-based semisupervised learning methods. In this paper, we propose a novel graph for Semisupervised Discriminant Analysis, which is called combined low-rank and k-nearest neighbor (LRKNN) graph. In our LRKNN graph, we map the data to the LR feature space and then the kNN is adopted to satisfy the algorithmic requirements of SDA. Since the low-rank representation can capture the global structure and the k-nearest neighbor algorithm can maximally preserve the local geometrical structure of the data, the LRKNN graph can significantly improve the performance of SDA. Extensive experiments on several real-world databases show that the proposed LRKNN graph is an efficient graph constructor, which can largely outperform other commonly used baselines. PMID:28316616

Heart murmur detection based on wavelet transformation and a synergy between artificial neural network and modified neighbor annealing methods.

PubMed

Eslamizadeh, Gholamhossein; Barati, Ramin

2017-05-01

Early recognition of heart disease plays a vital role in saving lives. Heart murmurs are one of the common heart problems. In this study, Artificial Neural Network (ANN) is trained with Modified Neighbor Annealing (MNA) to classify heart cycles into normal and murmur classes. Heart cycles are separated from heart sounds using wavelet transformer. The network inputs are features extracted from individual heart cycles, and two classification outputs. Classification accuracy of the proposed model is compared with five multilayer perceptron trained with Levenberg-Marquardt, Extreme-learning-machine, back-propagation, simulated-annealing, and neighbor-annealing algorithms. It is also compared with a Self-Organizing Map (SOM) ANN. The proposed model is trained and tested using real heart sounds available in the Pascal database to show the applicability of the proposed scheme. Also, a device to record real heart sounds has been developed and used for comparison purposes too. Based on the results of this study, MNA can be used to produce considerable results as a heart cycle classifier. Copyright © 2017 Elsevier B.V. All rights reserved.

An Investigation of Multidimensional Voice Program Parameters in Three Different Databases for Voice Pathology Detection and Classification.

PubMed

Al-Nasheri, Ahmed; Muhammad, Ghulam; Alsulaiman, Mansour; Ali, Zulfiqar; Mesallam, Tamer A; Farahat, Mohamed; Malki, Khalid H; Bencherif, Mohamed A

2017-01-01

Automatic voice-pathology detection and classification systems may help clinicians to detect the existence of any voice pathologies and the type of pathology from which patients suffer in the early stages. The main aim of this paper is to investigate Multidimensional Voice Program (MDVP) parameters to automatically detect and classify the voice pathologies in multiple databases, and then to find out which parameters performed well in these two processes. Samples of the sustained vowel /a/ of normal and pathological voices were extracted from three different databases, which have three voice pathologies in common. The selected databases in this study represent three distinct languages: (1) the Arabic voice pathology database; (2) the Massachusetts Eye and Ear Infirmary database (English database); and (3) the Saarbruecken Voice Database (German database). A computerized speech lab program was used to extract MDVP parameters as features, and an acoustical analysis was performed. The Fisher discrimination ratio was applied to rank the parameters. A t test was performed to highlight any significant differences in the means of the normal and pathological samples. The experimental results demonstrate a clear difference in the performance of the MDVP parameters using these databases. The highly ranked parameters also differed from one database to another. The best accuracies were obtained by using the three highest ranked MDVP parameters arranged according to the Fisher discrimination ratio: these accuracies were 99.68%, 88.21%, and 72.53% for the Saarbruecken Voice Database, the Massachusetts Eye and Ear Infirmary database, and the Arabic voice pathology database, respectively. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Ultracold fermions in a one-dimensional bipartite optical lattice: Metal-insulator transitions driven by shaking

NASA Astrophysics Data System (ADS)

Di Liberto, M.; Malpetti, D.; Japaridze, G. I.; Morais Smith, C.

2014-08-01

We theoretically investigate the behavior of a system of fermionic atoms loaded in a bipartite one-dimensional optical lattice that is under the action of an external time-periodic driving force. By using Floquet theory, an effective model is derived. The bare hopping coefficients are renormalized by zeroth-order Bessel functions of the first kind with different arguments for the nearest-neighbor and next-nearest-neighbor hopping. The insulating behavior characterizing the system at half filling in the absence of driving is dynamically suppressed, and for particular values of the driving parameter the system becomes either a standard metal or an unconventional metal with four Fermi points. The existence of the four-Fermi-point metal relies on the fact that, as a consequence of the shaking procedure, the next-nearest-neighbor hopping coefficients become significant compared to the nearest-neighbor ones. We use the bosonization technique to investigate the effect of on-site Hubbard interactions on the four-Fermi-point metal-insulator phase transition. Attractive interactions are expected to enlarge the regime of parameters where the unconventional metallic phase arises, whereas repulsive interactions reduce it. This metallic phase is known to be a Luther-Emery liquid (spin-gapped metal) for both repulsive and attractive interactions, contrary to the usual Hubbard model, which exhibits a Mott-insulator phase for repulsive interactions. Ultracold fermions in driven one-dimensional bipartite optical lattices provide an interesting platform for the realization of this long-studied four-Fermi-point unconventional metal.

GEMINI: a computationally-efficient search engine for large gene expression datasets.

PubMed

DeFreitas, Timothy; Saddiki, Hachem; Flaherty, Patrick

2016-02-24

Low-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query - a text-based string - is mismatched with the form of the target - a genomic profile. To improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an [Formula: see text] expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 10(5) samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec. GEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information.

A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower

PubMed Central

Du, Yuanfeng; Yang, Dongkai; Xiu, Chundi

2015-01-01

With the rapid development of WIFI technology, WIFI-based indoor positioning technology has been widely studied for location-based services. To solve the problems related to the signal strength database adopted in the widely used fingerprint positioning technology, we first introduce a new system framework in this paper, which includes a modified AP firmware and some cheap self-made WIFI sensor anchors. The periodically scanned reports regarding the neighboring APs and sensor anchors are sent to the positioning server and serve as the calibration points. Besides the calculation of correlations between the target points and the neighboring calibration points, we take full advantage of the important but easily overlooked feature that the signal attenuation model varies in different regions in the regression algorithm to get more accurate results. Thus, a novel method called RSSI Geography Weighted Regression (RGWR) is proposed to solve the fingerprint database construction problem. The average error of all the calibration points’ self-localization results will help to make the final decision of whether the database is the latest or has to be updated automatically. The effects of anchors on system performance are further researched to conclude that the anchors should be deployed at the locations that stand for the features of RSSI distributions. The proposed system is convenient for the establishment of practical positioning system and extensive experiments have been performed to validate that the proposed method is robust and manpower efficient. PMID:25868078

A novel method for constructing a WIFI positioning system with efficient manpower.

PubMed

Du, Yuanfeng; Yang, Dongkai; Xiu, Chundi

2015-04-10

With the rapid development of WIFI technology, WIFI-based indoor positioning technology has been widely studied for location-based services. To solve the problems related to the signal strength database adopted in the widely used fingerprint positioning technology, we first introduce a new system framework in this paper, which includes a modified AP firmware and some cheap self-made WIFI sensor anchors. The periodically scanned reports regarding the neighboring APs and sensor anchors are sent to the positioning server and serve as the calibration points. Besides the calculation of correlations between the target points and the neighboring calibration points, we take full advantage of the important but easily overlooked feature that the signal attenuation model varies in different regions in the regression algorithm to get more accurate results. Thus, a novel method called RSSI Geography Weighted Regression (RGWR) is proposed to solve the fingerprint database construction problem. The average error of all the calibration points' self-localization results will help to make the final decision of whether the database is the latest or has to be updated automatically. The effects of anchors on system performance are further researched to conclude that the anchors should be deployed at the locations that stand for the features of RSSI distributions. The proposed system is convenient for the establishment of practical positioning system and extensive experiments have been performed to validate that the proposed method is robust and manpower efficient.

Thermal rectification in mass-graded next-nearest-neighbor Fermi-Pasta-Ulam lattices

NASA Astrophysics Data System (ADS)

Romero-Bastida, M.; Miranda-Peña, Jorge-Orlando; López, Juan M.

2017-03-01

We study the thermal rectification efficiency, i.e., quantification of asymmetric heat flow, of a one-dimensional mass-graded anharmonic oscillator Fermi-Pasta-Ulam lattice both with nearest-neighbor (NN) and next-nearest-neighbor (NNN) interactions. The system presents a maximum rectification efficiency for a very precise value of the parameter that controls the coupling strength of the NNN interactions, which also optimizes the rectification figure when its dependence on mass asymmetry and temperature differences is considered. The origin of the enhanced rectification is the asymmetric local heat flow response as the heat reservoirs are swapped when a finely tuned NNN contribution is taken into account. A simple theoretical analysis gives an estimate of the optimal NNN coupling in excellent agreement with our simulation results.

Shifts due to quantum-mechanical interference from distant neighboring resonances for saturated fluorescence spectroscopy of the 23S to 23P intervals of helium

NASA Astrophysics Data System (ADS)

Marsman, A.; Hessels, E. A.; Horbatsch, M.

2014-04-01

Quantum-mechanical interference with distant neighboring resonances is found to cause shifts for precision saturated fluorescence spectroscopy of the atomic helium 23S-to-23P transitions. The shifts are significant (larger than the experimental uncertainties for measurements of the intervals) despite the fact that the neighboring resonances are separated from the measured resonances by 1400 and 20000 natural widths. The shifts depend strongly on experimental parameters such as the angular position of the fluorescence detector, the intensity and size of laser beams, and the properties of the atomic beam. These shifts must be considered for the ongoing program of determining the fine-structure constant from the helium 23P fine structure.

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE PAGES

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-06-24

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

The Statistical Power of the Cluster Randomized Block Design with Matched Pairs--A Simulation Study

ERIC Educational Resources Information Center

Dong, Nianbo; Lipsey, Mark

2010-01-01

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…

New Capabilities in the Astrophysics Multispectral Archive Search Engine

NASA Astrophysics Data System (ADS)

Cheung, C. Y.; Kelley, S.; Roussopoulos, N.

The Astrophysics Multispectral Archive Search Engine (AMASE) uses object-oriented database techniques to provide a uniform multi-mission and multi-spectral interface to search for data in the distributed archives. We describe our experience of porting AMASE from Illustra object-relational DBMS to the Informix Universal Data Server. New capabilities and utilities have been developed, including a spatial datablade that supports Nearest Neighbor queries.

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Accurate modeling of defects in graphene transport calculations

NASA Astrophysics Data System (ADS)

Linhart, Lukas; Burgdörfer, Joachim; Libisch, Florian

2018-01-01

We present an approach for embedding defect structures modeled by density functional theory into large-scale tight-binding simulations. We extract local tight-binding parameters for the vicinity of the defect site using Wannier functions. In the transition region between the bulk lattice and the defect the tight-binding parameters are continuously adjusted to approach the bulk limit far away from the defect. This embedding approach allows for an accurate high-level treatment of the defect orbitals using as many as ten nearest neighbors while keeping a small number of nearest neighbors in the bulk to render the overall computational cost reasonable. As an example of our approach, we consider an extended graphene lattice decorated with Stone-Wales defects, flower defects, double vacancies, or silicon substitutes. We predict distinct scattering patterns mirroring the defect symmetries and magnitude that should be experimentally accessible.

Improved Fuzzy K-Nearest Neighbor Using Modified Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Jamaluddin; Siringoringo, Rimbun

2017-12-01

Fuzzy k-Nearest Neighbor (FkNN) is one of the most powerful classification methods. The presence of fuzzy concepts in this method successfully improves its performance on almost all classification issues. The main drawbackof FKNN is that it is difficult to determine the parameters. These parameters are the number of neighbors (k) and fuzzy strength (m). Both parameters are very sensitive. This makes it difficult to determine the values of ‘m’ and ‘k’, thus making FKNN difficult to control because no theories or guides can deduce how proper ‘m’ and ‘k’ should be. This study uses Modified Particle Swarm Optimization (MPSO) to determine the best value of ‘k’ and ‘m’. MPSO is focused on the Constriction Factor Method. Constriction Factor Method is an improvement of PSO in order to avoid local circumstances optima. The model proposed in this study was tested on the German Credit Dataset. The test of the data/The data test has been standardized by UCI Machine Learning Repository which is widely applied to classification problems. The application of MPSO to the determination of FKNN parameters is expected to increase the value of classification performance. Based on the experiments that have been done indicating that the model offered in this research results in a better classification performance compared to the Fk-NN model only. The model offered in this study has an accuracy rate of 81%, while. With using Fk-NN model, it has the accuracy of 70%. At the end is done comparison of research model superiority with 2 other classification models;such as Naive Bayes and Decision Tree. This research model has a better performance level, where Naive Bayes has accuracy 75%, and the decision tree model has 70%

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

A Component-Based Diffusion Model With Structural Diversity for Social Networks.

PubMed

Qing Bao; Cheung, William K; Yu Zhang; Jiming Liu

2017-04-01

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.

The influence of further-neighbor spin-spin interaction on a ground state of 2D coupled spin-electron model in a magnetic field

NASA Astrophysics Data System (ADS)

Čenčariková, Hana; Strečka, Jozef; Gendiar, Andrej; Tomašovičová, Natália

2018-05-01

An exhaustive ground-state analysis of extended two-dimensional (2D) correlated spin-electron model consisting of the Ising spins localized on nodal lattice sites and mobile electrons delocalized over pairs of decorating sites is performed within the framework of rigorous analytical calculations. The investigated model, defined on an arbitrary 2D doubly decorated lattice, takes into account the kinetic energy of mobile electrons, the nearest-neighbor Ising coupling between the localized spins and mobile electrons, the further-neighbor Ising coupling between the localized spins and the Zeeman energy. The ground-state phase diagrams are examined for a wide range of model parameters for both ferromagnetic as well as antiferromagnetic interaction between the nodal Ising spins and non-zero value of external magnetic field. It is found that non-zero values of further-neighbor interaction leads to a formation of new quantum states as a consequence of competition between all considered interaction terms. Moreover, the new quantum states are accompanied with different magnetic features and thus, several kinds of field-driven phase transitions are observed.

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Gender classification from face images by using local binary pattern and gray-level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Uzbaş, Betül; Arslan, Ahmet

2018-04-01

Gender is an important step for human computer interactive processes and identification. Human face image is one of the important sources to determine gender. In the present study, gender classification is performed automatically from facial images. In order to classify gender, we propose a combination of features that have been extracted face, eye and lip regions by using a hybrid method of Local Binary Pattern and Gray-Level Co-Occurrence Matrix. The features have been extracted from automatically obtained face, eye and lip regions. All of the extracted features have been combined and given as input parameters to classification methods (Support Vector Machine, Artificial Neural Networks, Naive Bayes and k-Nearest Neighbor methods) for gender classification. The Nottingham Scan face database that consists of the frontal face images of 100 people (50 male and 50 female) is used for this purpose. As the result of the experimental studies, the highest success rate has been achieved as 98% by using Support Vector Machine. The experimental results illustrate the efficacy of our proposed method.

Gene Graphics: a genomic neighborhood data visualization web application.

PubMed

Harrison, Katherine J; Crécy-Lagard, Valérie de; Zallot, Rémi

2018-04-15

The examination of gene neighborhood is an integral part of comparative genomics but no tools to produce publication quality graphics of gene clusters are available. Gene Graphics is a straightforward web application for creating such visuals. Supported inputs include National Center for Biotechnology Information gene and protein identifiers with automatic fetching of neighboring information, GenBank files and data extracted from the SEED database. Gene representations can be customized for many parameters including gene and genome names, colors and sizes. Gene attributes can be copied and pasted for rapid and user-friendly customization of homologous genes between species. In addition to Portable Network Graphics and Scalable Vector Graphics, produced representations can be exported as Tagged Image File Format or Encapsulated PostScript, formats that are standard for publication. Hands-on tutorials with real life examples inspired from publications are available for training. Gene Graphics is freely available at https://katlabs.cc/genegraphics/ and source code is hosted at https://github.com/katlabs/genegraphics. katherinejh@ufl.edu or remizallot@ufl.edu. Supplementary data are available at Bioinformatics online.

A hierarchical stress release model for synthetic seismicity

NASA Astrophysics Data System (ADS)

Bebbington, Mark

1997-06-01

We construct a stochastic dynamic model for synthetic seismicity involving stochastic stress input, release, and transfer in an environment of heterogeneous strength and interacting segments. The model is not fault-specific, having a number of adjustable parameters with physical interpretation, namely, stress relaxation, stress transfer, stress dissipation, segment structure, strength, and strength heterogeneity, which affect the seismicity in various ways. Local parameters are chosen to be consistent with large historical events, other parameters to reproduce bulk seismicity statistics for the fault as a whole. The one-dimensional fault is divided into a number of segments, each comprising a varying number of nodes. Stress input occurs at each node in a simple random process, representing the slow buildup due to tectonic plate movements. Events are initiated, subject to a stochastic hazard function, when the stress on a node exceeds the local strength. An event begins with the transfer of excess stress to neighboring nodes, which may in turn transfer their excess stress to the next neighbor. If the event grows to include the entire segment, then most of the stress on the segment is transferred to neighboring segments (or dissipated) in a characteristic event. These large events may themselves spread to other segments. We use the Middle America Trench to demonstrate that this model, using simple stochastic stress input and triggering mechanisms, can produce behavior consistent with the historical record over five units of magnitude. We also investigate the effects of perturbing various parameters in order to show how the model might be tailored to a specific fault structure. The strength of the model lies in this ability to reproduce the behavior of a general linear fault system through the choice of a relatively small number of parameters. It remains to develop a procedure for estimating the internal state of the model from the historical observations in order to use the model for forward prediction.

Physiological Parameters Database for PBPK Modeling (External Review Draft)

EPA Science Inventory

EPA released for public comment a physiological parameters database (created using Microsoft ACCESS) intended to be used in PBPK modeling. The database contains physiological parameter values for humans from early childhood through senescence. It also contains similar data for an...

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

Local intensity area descriptor for facial recognition in ideal and noise conditions

NASA Astrophysics Data System (ADS)

Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

Chemical Space: Big Data Challenge for Molecular Diversity.

PubMed

Awale, Mahendra; Visini, Ricardo; Probst, Daniel; Arús-Pous, Josep; Reymond, Jean-Louis

2017-10-25

Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.

Comprehensive thermodynamic analysis of 3′ double-nucleotide overhangs neighboring Watson–Crick terminal base pairs

PubMed Central

O'Toole, Amanda S.; Miller, Stacy; Haines, Nathan; Zink, M. Coleen; Serra, Martin J.

2006-01-01

Thermodynamic parameters are reported for duplex formation of 48 self-complementary RNA duplexes containing Watson–Crick terminal base pairs (GC, AU and UA) with all 16 possible 3′ double-nucleotide overhangs; mimicking the structures of short interfering RNAs (siRNA) and microRNAs (miRNA). Based on nearest-neighbor analysis, the addition of a second dangling nucleotide to a single 3′ dangling nucleotide increases stability of duplex formation up to 0.8 kcal/mol in a sequence dependent manner. Results from this study in conjunction with data from a previous study [A. S. O'Toole, S. Miller and M. J. Serra (2005) RNA, 11, 512.] allows for the development of a refined nearest-neighbor model to predict the influence of 3′ double-nucleotide overhangs on the stability of duplex formation. The model improves the prediction of free energy and melting temperature when tested against five oligomers with various core duplex sequences. Phylogenetic analysis of naturally occurring miRNAs was performed to support our results. Selection of the effector miR strand of the mature miRNA duplex appears to be dependent upon the identity of the 3′ double-nucleotide overhang. Thermodynamic parameters for 3′ single terminal overhangs adjacent to a UA pair are also presented. PMID:16820533

Blocking performance approximation in flexi-grid networks

NASA Astrophysics Data System (ADS)

Ge, Fei; Tan, Liansheng

2016-12-01

The blocking probability to the path requests is an important issue in flexible bandwidth optical communications. In this paper, we propose a blocking probability approximation method of path requests in flexi-grid networks. It models the bundled neighboring carrier allocation with a group of birth-death processes and provides a theoretical analysis to the blocking probability under variable bandwidth traffic. The numerical results show the effect of traffic parameters to the blocking probability of path requests. We use the first fit algorithm in network nodes to allocate neighboring carriers to path requests in simulations, and verify approximation results.

[1012.5676] The Exoplanet Orbit Database

Science.gov Websites

: The Exoplanet Orbit Database Authors: Jason T Wright, Onsi Fakhouri, Geoffrey W. Marcy, Eunkyu Han present a database of well determined orbital parameters of exoplanets. This database comprises parameters, and the method used for the planets discovery. This Exoplanet Orbit Database includes all planets

Shifts due to quantum-mechanical interference from distant neighboring resonances for saturated fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Marsman, Alain; Horbatsch, Marko; Hessels, Eric A.

2014-05-01

Quantum-mechanical interference with distant neighboring resonances is found to cause shifts for precision saturated fluorescence spectroscopy of the atomic helium 23 S -to- 23 P transitions. The shifts are significant (larger than the experimental uncertainties for measurements of the intervals) despite the fact that the neighboring resonances are separated from the measured resonances by 1400 and 20 000 natural widths. The shifts depend strongly on experimental parameters such as the angular position of the fluorescence detector and the intensity and size of laser beams. These shifts must be considered for the ongoing program of determining the fine-structure constant from the helium 23 P fine structure. The work represents the first study of such interference shifts for saturated fluorescence spectroscopy and follows up on our previous study of similar shifts for laser spectroscopy. This work is supported by NSERC, CRC, ORF, CFI, NIST and SHARCNET.

Social dilemma alleviated by sharing the gains with immediate neighbors

NASA Astrophysics Data System (ADS)

Wu, Zhi-Xi; Yang, Han-Xin

2014-01-01

We study the evolution of cooperation in the evolutionary spatial prisoner's dilemma game (PDG) and snowdrift game (SG), within which a fraction α of the payoffs of each player gained from direct game interactions is shared equally by the immediate neighbors. The magnitude of the parameter α therefore characterizes the degree of the relatedness among the neighboring players. By means of extensive Monte Carlo simulations as well as an extended mean-field approximation method, we trace the frequency of cooperation in the stationary state. We find that plugging into relatedness can significantly promote the evolution of cooperation in the context of both studied games. Unexpectedly, cooperation can be more readily established in the spatial PDG than that in the spatial SG, given that the degree of relatedness and the cost-to-benefit ratio of mutual cooperation are properly formulated. The relevance of our model with the stakeholder theory is also briefly discussed.

Parrondo's games based on complex networks and the paradoxical effect.

PubMed

Ye, Ye; Wang, Lu; Xie, Nenggang

2013-01-01

Parrondo's games were first constructed using a simple tossing scenario, which demonstrates the following paradoxical situation: in sequences of games, a winning expectation may be obtained by playing the games in a random order, although each game (game A or game B) in the sequence may result in losing when played individually. The available Parrondo's games based on the spatial niche (the neighboring environment) are applied in the regular networks. The neighbors of each node are the same in the regular graphs, whereas they are different in the complex networks. Here, Parrondo's model based on complex networks is proposed, and a structure of game B applied in arbitrary topologies is constructed. The results confirm that Parrondo's paradox occurs. Moreover, the size of the region of the parameter space that elicits Parrondo's paradox depends on the heterogeneity of the degree distributions of the networks. The higher heterogeneity yields a larger region of the parameter space where the strong paradox occurs. In addition, we use scale-free networks to show that the network size has no significant influence on the region of the parameter space where the strong or weak Parrondo's paradox occurs. The region of the parameter space where the strong Parrondo's paradox occurs reduces slightly when the average degree of the network increases.

Local structure of dilute aqueous DMSO solutions, as seen from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Idrissi, Abdenacer; Marekha, Bogdan A.; Barj, Mohammed; Miannay, François Alexandre; Takamuku, Toshiyuki; Raptis, Vasilios; Samios, Jannis; Jedlovszky, Pál

2017-06-01

The information about the structure of dimethyl sulfoxide (DMSO)-water mixtures at relatively low DMSO mole fractions is an important step in order to understand their cryoprotective properties as well as the solvation process of proteins and amino acids. Classical MD simulations, using the potential model combination that best reproduces the free energy of mixing of these compounds, are used to analyze the local structure of DMSO-water mixtures at DMSO mole fractions below 0.2. Significant changes in the local structure of DMSO are observed around the DMSO mole fraction of 0.1. The array of evidence, based on the cluster and the metric and topological parameters of the Voronoi polyhedra distributions, indicates that these changes are associated with the simultaneous increase of the number of DMSO-water and decrease of water-water hydrogen bonds with increasing DMSO concentration. The inversion between the dominance of these two types of H-bonds occurs around XDMSO = 0.1, above which the DMSO-DMSO interactions also start playing an important role. In other words, below the DMSO mole fraction of 0.1, DMSO molecules are mainly solvated by water molecules, while above it, their solvation shell consists of a mixture of water and DMSO. The trigonal, tetrahedral, and trigonal bipyramidal distributions of water shift to lower corresponding order parameter values indicating the loosening of these orientations. Adding DMSO does not affect the hydrogen bonding between a reference water molecule and its first neighbor hydrogen bonded water molecules, while it increases the bent hydrogen bond geometry involving the second ones. The close-packed local structure of the third, fourth, and fifth water neighbors also is reinforced. In accordance with previous theoretical and experimental data, the hydrogen bonding between water and the first, the second, and the third DMSO neighbors is stronger than that with its corresponding water neighbors. At a given DMSO mole fraction, the behavior of the intensity of the high orientational order parameter values indicates that water molecules are more ordered in the vicinity of the hydrophilic group while their structure is close-packed near the hydrophobic group of DMSO.

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.

Equilibrium polymerization on the equivalent-neighbor lattice

NASA Technical Reports Server (NTRS)

Kaufman, Miron

1989-01-01

The equilibrium polymerization problem is solved exactly on the equivalent-neighbor lattice. The Flory-Huggins (Flory, 1986) entropy of mixing is exact for this lattice. The discrete version of the n-vector model is verified when n approaches 0 is equivalent to the equal reactivity polymerization process in the whole parameter space, including the polymerized phase. The polymerization processes for polymers satisfying the Schulz (1939) distribution exhibit nonuniversal critical behavior. A close analogy is found between the polymerization problem of index the Schulz r and the Bose-Einstein ideal gas in d = -2r dimensions, with the critical polymerization corresponding to the Bose-Einstein condensation.

Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

NASA Astrophysics Data System (ADS)

Wu, Binlin; Nebylitsa, Samantha V.; Mukherjee, Sushmita; Jain, Manu

2015-02-01

In clinical practice, histopathological analysis of biopsied tissue is the main method for bladder cancer diagnosis and prognosis. The diagnosis is performed by a pathologist based on the morphological features in the image of a hematoxylin and eosin (HE) stained tissue sample. This manuscript proposes algorithms to perform morphometric analysis on the HE images, quantify the features in the images, and discriminate bladder cancers with different grades, i.e. high grade and low grade. The nuclei are separated from the background and other types of cells such as red blood cells (RBCs) and immune cells using manual outlining, color deconvolution and image segmentation. A mask of nuclei is generated for each image for quantitative morphometric analysis. The features of the nuclei in the mask image including size, shape, orientation, and their spatial distributions are measured. To quantify local clustering and alignment of nuclei, we propose a 1-nearest-neighbor (1-NN) algorithm which measures nearest neighbor distance and nearest neighbor parallelism. The global distributions of the features are measured using statistics of the proposed parameters. A linear support vector machine (SVM) algorithm is used to classify the high grade and low grade bladder cancers. The results show using a particular group of nuclei such as large ones, and combining multiple parameters can achieve better discrimination. This study shows the proposed approach can potentially help expedite pathological diagnosis by triaging potentially suspicious biopsies.

Synergistic effects in threshold models on networks

NASA Astrophysics Data System (ADS)

Juul, Jonas S.; Porter, Mason A.

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Morphological identification and COI barcodes of adult flies help determine species identities of chironomid larvae (Diptera, Chironomidae).

PubMed

Failla, A J; Vasquez, A A; Hudson, P; Fujimoto, M; Ram, J L

2016-02-01

Establishing reliable methods for the identification of benthic chironomid communities is important due to their significant contribution to biomass, ecology and the aquatic food web. Immature larval specimens are more difficult to identify to species level by traditional morphological methods than their fully developed adult counterparts, and few keys are available to identify the larval species. In order to develop molecular criteria to identify species of chironomid larvae, larval and adult chironomids from Western Lake Erie were subjected to both molecular and morphological taxonomic analysis. Mitochondrial cytochrome c oxidase I (COI) barcode sequences of 33 adults that were identified to species level by morphological methods were grouped with COI sequences of 189 larvae in a neighbor-joining taxon-ID tree. Most of these larvae could be identified only to genus level by morphological taxonomy (only 22 of the 189 sequenced larvae could be identified to species level). The taxon-ID tree of larval sequences had 45 operational taxonomic units (OTUs, defined as clusters with >97% identity or individual sequences differing from nearest neighbors by >3%; supported by analysis of all larval pairwise differences), of which seven could be identified to species or 'species group' level by larval morphology. Reference sequences from the GenBank and BOLD databases assigned six larval OTUs with presumptive species level identifications and confirmed one previously assigned species level identification. Sequences from morphologically identified adults in the present study grouped with and further classified the identity of 13 larval OTUs. The use of morphological identification and subsequent DNA barcoding of adult chironomids proved to be beneficial in revealing possible species level identifications of larval specimens. Sequence data from this study also contribute to currently inadequate public databases relevant to the Great Lakes region, while the neighbor-joining analysis reported here describes the application and confirmation of a useful tool that can accelerate identification and bioassessment of chironomid communities.

Molecular characterization and phylogenetic relatedness of dog-derived Rabies Viruses circulating in Cameroon between 2010 and 2016.

PubMed

Sadeuh-Mba, Serge Alain; Momo, Jean Blaise; Besong, Laura; Loul, Sévérin; Njouom, Richard

2017-10-01

Rabies is enzootic among dog populations in some parts of Cameroon and the risk of human rabies is thought to be steadily high in these regions. However, the molecular epidemiology of circulating Rabies Virus (RABV) has been hardly considered in Cameroon as well as in most neighboring central African countries. To address this fundamental gap, 76 nucleoprotein (N) gene sequences of dog-derived RABV were obtained from 100 brain specimens sampled in Cameroon from 2010 to 2016. Studied sequences were subjected to molecular and phylogenetic analyses with reference strains retrieved from databases. The 71 studied Africa-1 isolates displayed 93.5-100% nucleotide (nt) and 98.3-100% amino-acid (aa) identities to each other while, the 5 studied Africa-2 isolates shared 99.4-99.7% sequence similarities at nt and aa levels. Maximum Likelihood based phylogenies inferred from nucleotide sequences confirmed all studied RABV isolates as members of the dog-related species 1 of the Lyssavirus genus. Individual isolates could be unambiguously assigned as either the Africa-1 subclade of the Cosmopolitan clade or the Africa 2 clade. The Africa-1 subclade appeared to be more prevalent and diversified. Indeed, 70 studied isolates segregated into 3 distinct circulating variants within Africa-1a lineage while a unique isolate was strikingly related to the Africa-1b lineage known to be prevalent in the neighboring Central African Republic and eastern Africa. Interestingly, all five Africa-2 isolates fell into the group-E lineage even though they appeared to be loosely related to databases available reference RABV; including those previously documented in Cameroon. This study uncovered the co-circulation of several Africa-1 and Africa-2 lineages in the southern regions of Cameroon. Striking phylogenetic outcasts to the geographic differentiation of RABV variants indicated that importation from close regions or neighboring countries apparently contributes to the sustainment of the enzootic cycle of domestic rabies in Cameroon.

Morphological identification and COI barcodes of adult flies help determine species identities of chironomid larvae (Diptera, Chironomidae)

USGS Publications Warehouse

Failla, Andrew Joseph; Vasquez, Adrian Amelio; Hudson, Patrick L.; Fujimoto, Masanori; Ram, Jeffrey L.

2016-01-01

Establishing reliable methods for the identification of benthic chironomid communities is important due to their significant contribution to biomass, ecology and the aquatic food web. Immature larval specimens are more difficult to identify to species level by traditional morphological methods than their fully developed adult counterparts, and few keys are available to identify the larval species. In order to develop molecular criteria to identify species of chironomid larvae, larval and adult chironomids from Western Lake Erie were subjected to both molecular and morphological taxonomic analysis. Mitochondrial cytochrome c oxidase I (COI) barcode sequences of 33 adults that were identified to species level by morphological methods were grouped with COI sequences of 189 larvae in a neighbor-joining taxon-ID tree. Most of these larvae could be identified only to genus level by morphological taxonomy (only 22 of the 189 sequenced larvae could be identified to species level). The taxon-ID tree of larval sequences had 45 operational taxonomic units (OTUs, defined as clusters with >97% identity or individual sequences differing from nearest neighbors by >3%; supported by analysis of all larval pairwise differences), of which seven could be identified to species or ‘species group’ level by larval morphology. Reference sequences from the GenBank and BOLD databases assigned six larval OTUs with presumptive species level identifications and confirmed one previously assigned species level identification. Sequences from morphologically identified adults in the present study grouped with and further classified the identity of 13 larval OTUs. The use of morphological identification and subsequent DNA barcoding of adult chironomids proved to be beneficial in revealing possible species level identifications of larval specimens. Sequence data from this study also contribute to currently inadequate public databases relevant to the Great Lakes region, while the neighbor-joining analysis reported here describes the application and confirmation of a useful tool that can accelerate identification and bioassesment of chironomid communities.

Molecular characterization and phylogenetic relatedness of dog-derived Rabies Viruses circulating in Cameroon between 2010 and 2016

PubMed Central

Momo, Jean Blaise; Besong, Laura; Loul, Sévérin; Njouom, Richard

2017-01-01

Rabies is enzootic among dog populations in some parts of Cameroon and the risk of human rabies is thought to be steadily high in these regions. However, the molecular epidemiology of circulating Rabies Virus (RABV) has been hardly considered in Cameroon as well as in most neighboring central African countries. To address this fundamental gap, 76 nucleoprotein (N) gene sequences of dog-derived RABV were obtained from 100 brain specimens sampled in Cameroon from 2010 to 2016. Studied sequences were subjected to molecular and phylogenetic analyses with reference strains retrieved from databases. The 71 studied Africa-1 isolates displayed 93.5–100% nucleotide (nt) and 98.3–100% amino-acid (aa) identities to each other while, the 5 studied Africa-2 isolates shared 99.4–99.7% sequence similarities at nt and aa levels. Maximum Likelihood based phylogenies inferred from nucleotide sequences confirmed all studied RABV isolates as members of the dog-related species 1 of the Lyssavirus genus. Individual isolates could be unambiguously assigned as either the Africa-1 subclade of the Cosmopolitan clade or the Africa 2 clade. The Africa-1 subclade appeared to be more prevalent and diversified. Indeed, 70 studied isolates segregated into 3 distinct circulating variants within Africa-1a lineage while a unique isolate was strikingly related to the Africa-1b lineage known to be prevalent in the neighboring Central African Republic and eastern Africa. Interestingly, all five Africa-2 isolates fell into the group-E lineage even though they appeared to be loosely related to databases available reference RABV; including those previously documented in Cameroon. This study uncovered the co-circulation of several Africa-1 and Africa-2 lineages in the southern regions of Cameroon. Striking phylogenetic outcasts to the geographic differentiation of RABV variants indicated that importation from close regions or neighboring countries apparently contributes to the sustainment of the enzootic cycle of domestic rabies in Cameroon. PMID:29084223

The effect of lexical factors on recall from working memory: Generalizing the neighborhood size effect.

PubMed

Derraugh, Lesley S; Neath, Ian; Surprenant, Aimée M; Beaudry, Olivia; Saint-Aubin, Jean

2017-03-01

The word-length effect, the finding that lists of short words are better recalled than lists of long words, is 1 of the 4 benchmark phenomena that guided development of the phonological loop component of working memory. However, previous work has noted a confound in word-length studies: The short words used had more orthographic neighbors (valid words that can be made by changing a single letter in the target word) than long words. The confound is that words with more neighbors are better recalled than otherwise comparable words with fewer neighbors. Two experiments are reported that address criticisms of the neighborhood-size account of the word-length effect by (1) testing 2 new stimulus sets, (2) using open rather than closed pools of words, and (3) using stimuli from a language other than English. In both experiments, words from large neighborhoods were better recalled than words from small neighborhoods. The results add to the growing number of studies demonstrating the substantial contribution of long-term memory to what have traditionally been identified as working memory tasks. The data are more easily explained by models incorporating the concept of redintegration rather than by frameworks such as the phonological loop that posit decay offset by rehearsal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Parallel Ghosting Algorithm for The Flexible Distributed Mesh Database

DOE PAGES

Mubarak, Misbah; Seol, Seegyoung; Lu, Qiukai; ...

2013-01-01

Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in amore » 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can create n number of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.« less

Band structure and orbital character of monolayer MoS2 with eleven-band tight-binding model

NASA Astrophysics Data System (ADS)

Shahriari, Majid; Ghalambor Dezfuli, Abdolmohammad; Sabaeian, Mohammad

2018-02-01

In this paper, based on a tight-binding (TB) model, first we present the calculations of eigenvalues as band structure and then present the eigenvectors as probability amplitude for finding electron in atomic orbitals for monolayer MoS2 in the first Brillouin zone. In these calculations we are considering hopping processes between the nearest-neighbor Mo-S, the next nearest-neighbor in-plan Mo-Mo, and the next nearest-neighbor in-plan and out-of-plan S-S atoms in a three-atom based unit cell of two-dimensional rhombic MoS2. The hopping integrals have been solved in terms of Slater-Koster and crystal field parameters. These parameters are calculated by comparing TB model with the density function theory (DFT) in the high-symmetry k-points (i.e. the K- and Γ-points). In our TB model all the 4d Mo orbitals and the 3p S orbitals are considered and detailed analysis of the orbital character of each energy level at the main high-symmetry points of the Brillouin zone is described. In comparison with DFT calculations, our results of TB model show a very good agreement for bands near the Fermi level. However for other bands which are far from the Fermi level, some discrepancies between our TB model and DFT calculations are observed. Upon the accuracy of Slater-Koster and crystal field parameters, on the contrary of DFT, our model provide enough accuracy to calculate all allowed transitions between energy bands that are very crucial for investigating the linear and nonlinear optical properties of monolayer MoS2.

Using an image-extended relational database to support content-based image retrieval in a PACS.

PubMed

Traina, Caetano; Traina, Agma J M; Araújo, Myrian R B; Bueno, Josiane M; Chino, Fabio J T; Razente, Humberto; Azevedo-Marques, Paulo M

2005-12-01

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.

Establishment and Assessment of Plasma Disruption and Warning Databases from EAST

NASA Astrophysics Data System (ADS)

Wang, Bo; Robert, Granetz; Xiao, Bingjia; Li, Jiangang; Yang, Fei; Li, Junjun; Chen, Dalong

2016-12-01

Disruption database and disruption warning database of the EAST tokamak had been established by a disruption research group. The disruption database, based on Structured Query Language (SQL), comprises 41 disruption parameters, which include current quench characteristics, EFIT equilibrium characteristics, kinetic parameters, halo currents, and vertical motion. Presently most disruption databases are based on plasma experiments of non-superconducting tokamak devices. The purposes of the EAST database are to find disruption characteristics and disruption statistics to the fully superconducting tokamak EAST, to elucidate the physics underlying tokamak disruptions, to explore the influence of disruption on superconducting magnets and to extrapolate toward future burning plasma devices. In order to quantitatively assess the usefulness of various plasma parameters for predicting disruptions, a similar SQL database to Alcator C-Mod for EAST has been created by compiling values for a number of proposed disruption-relevant parameters sampled from all plasma discharges in the 2015 campaign. The detailed statistic results and analysis of two databases on the EAST tokamak are presented. supported by the National Magnetic Confinement Fusion Science Program of China (No. 2014GB103000)

Detection and Rectification of Distorted Fingerprints.

PubMed

Si, Xuanbin; Feng, Jianjiang; Zhou, Jie; Luo, Yuxuan

2015-03-01

Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watchlist and deduplication applications. In such applications, malicious users may purposely distort their fingerprints to evade identification. In this paper, we proposed novel algorithms to detect and rectify skin distortion based on a single fingerprint image. Distortion detection is viewed as a two-class classification problem, for which the registered ridge orientation map and period map of a fingerprint are used as the feature vector and a SVM classifier is trained to perform the classification task. Distortion rectification (or equivalently distortion field estimation) is viewed as a regression problem, where the input is a distorted fingerprint and the output is the distortion field. To solve this problem, a database (called reference database) of various distorted reference fingerprints and corresponding distortion fields is built in the offline stage, and then in the online stage, the nearest neighbor of the input fingerprint is found in the reference database and the corresponding distortion field is used to transform the input fingerprint into a normal one. Promising results have been obtained on three databases containing many distorted fingerprints, namely FVC2004 DB1, Tsinghua Distorted Fingerprint database, and the NIST SD27 latent fingerprint database.

AACSD: An atomistic analyzer for crystal structure and defects

NASA Astrophysics Data System (ADS)

Liu, Z. R.; Zhang, R. F.

2018-01-01

We have developed an efficient command-line program named AACSD (Atomistic Analyzer for Crystal Structure and Defects) for the post-analysis of atomic configurations generated by various atomistic simulation codes. The program has implemented not only the traditional filter methods like the excess potential energy (EPE), the centrosymmetry parameter (CSP), the common neighbor analysis (CNA), the common neighborhood parameter (CNP), the bond angle analysis (BAA), and the neighbor distance analysis (NDA), but also the newly developed ones including the modified centrosymmetry parameter (m-CSP), the orientation imaging map (OIM) and the local crystallographic orientation (LCO). The newly proposed OIM and LCO methods have been extended for all three crystal structures including face centered cubic, body centered cubic and hexagonal close packed. More specially, AACSD can be easily used for the atomistic analysis of metallic nanocomposite with each phase to be analyzed independently, which provides a unique pathway to capture their dynamic evolution of various defects on the fly. In this paper, we provide not only a throughout overview on various theoretical methods and their implementation into AACSD program, but some critical evaluations, specific testing and applications, demonstrating the capability of the program on each functionality.

Linear model for fast background subtraction in oligonucleotide microarrays.

PubMed

Kroll, K Myriam; Barkema, Gerard T; Carlon, Enrico

2009-11-16

One important preprocessing step in the analysis of microarray data is background subtraction. In high-density oligonucleotide arrays this is recognized as a crucial step for the global performance of the data analysis from raw intensities to expression values. We propose here an algorithm for background estimation based on a model in which the cost function is quadratic in a set of fitting parameters such that minimization can be performed through linear algebra. The model incorporates two effects: 1) Correlated intensities between neighboring features in the chip and 2) sequence-dependent affinities for non-specific hybridization fitted by an extended nearest-neighbor model. The algorithm has been tested on 360 GeneChips from publicly available data of recent expression experiments. The algorithm is fast and accurate. Strong correlations between the fitted values for different experiments as well as between the free-energy parameters and their counterparts in aqueous solution indicate that the model captures a significant part of the underlying physical chemistry.

Terahertz metasurfaces with a high refractive index enhanced by the strong nearest neighbor coupling.

PubMed

Tan, Siyu; Yan, Fengping; Singh, Leena; Cao, Wei; Xu, Ningning; Hu, Xiang; Singh, Ranjan; Wang, Mingwei; Zhang, Weili

2015-11-02

The realization of high refractive index is of significant interest in optical imaging with enhanced resolution. Strongly coupled subwavelength resonators were proposed and demonstrated at both optical and terahertz frequencies to enhance the refractive index due to large induced dipole moment in meta-atoms. Here, we report an alternative design for flexible free-standing terahertz metasurface in the strong coupling regime where we experimentally achieve a peak refractive index value of 14.36. We also investigate the impact of the nearest neighbor coupling in the form of frequency tuning and enhancement of the peak refractive index. We provide an analytical circuit model to explain the impact of geometrical parameters and coupling on the effective refractive index of the metasurface. The proposed meta-atom structure enables tailoring of the peak refractive index based on nearest neighbor coupling and this property offers tremendous design flexibility for transformation optics and other index-gradient devices at terahertz frequencies.

Phase transitions and critical properties in the antiferromagnetic Ising model on a layered triangular lattice with allowance for intralayer next-nearest-neighbor interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badiev, M. K., E-mail: m-zagir@mail.ru; Murtazaev, A. K.; Ramazanov, M. K.

2016-10-15

The phase transitions (PTs) and critical properties of the antiferromagnetic Ising model on a layered (stacked) triangular lattice have been studied by the Monte Carlo method using a replica algorithm with allowance for the next-nearest-neighbor interactions. The character of PTs is analyzed using the histogram technique and the method of Binder cumulants. It is established that the transition from the disordered to paramagnetic phase in the adopted model is a second-order PT. Static critical exponents of the heat capacity (α), susceptibility (γ), order parameter (β), and correlation radius (ν) and the Fischer exponent η are calculated using the finite-size scalingmore » theory. It is shown that (i) the antiferromagnetic Ising model on a layered triangular lattice belongs to the XY universality class of critical behavior and (ii) allowance for the intralayer interactions of next-nearest neighbors in the adopted model leads to a change in the universality class of critical behavior.« less

Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

NASA Astrophysics Data System (ADS)

Chao, LIANG; Ling-yao, JIA; Dong-cheng, SHI

2017-01-01

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.

EBSDinterp 1.0: A MATLAB® Program to Perform Microstructurally Constrained Interpolation of EBSD Data.

PubMed

Pearce, Mark A

2015-08-01

EBSDinterp is a graphic user interface (GUI)-based MATLAB® program to perform microstructurally constrained interpolation of nonindexed electron backscatter diffraction data points. The area available for interpolation is restricted using variations in pattern quality or band contrast (BC). Areas of low BC are not available for interpolation, and therefore cannot be erroneously filled by adjacent grains "growing" into them. Points with the most indexed neighbors are interpolated first and the required number of neighbors is reduced with each successive round until a minimum number of neighbors is reached. Further iterations allow more data points to be filled by reducing the BC threshold. This method ensures that the best quality points (those with high BC and most neighbors) are interpolated first, and that the interpolation is restricted to grain interiors before adjacent grains are grown together to produce a complete microstructure. The algorithm is implemented through a GUI, taking advantage of MATLAB®'s parallel processing toolbox to perform the interpolations rapidly so that a variety of parameters can be tested to ensure that the final microstructures are robust and artifact-free. The software is freely available through the CSIRO Data Access Portal (doi:10.4225/08/5510090C6E620) as both a compiled Windows executable and as source code.

Highly Anisotropic Magnon Dispersion in Ca_{2}RuO_{4}: Evidence for Strong Spin Orbit Coupling.

PubMed

Kunkemöller, S; Khomskii, D; Steffens, P; Piovano, A; Nugroho, A A; Braden, M

2015-12-11

The magnon dispersion in Ca_{2}RuO_{4} has been determined by inelastic neutron scattering on single crytals containing 1% of Ti. The dispersion is well described by a conventional Heisenberg model suggesting a local moment model with nearest neighbor interaction of J=8  meV. Nearest and next-nearest neighbor interaction as well as interlayer coupling parameters are required to properly describe the entire dispersion. Spin-orbit coupling induces a very large anisotropy gap in the magnetic excitations in apparent contrast with a simple planar magnetic model. Orbital ordering breaking tetragonal symmetry, and strong spin-orbit coupling can thus be identified as important factors in this system.

Fidelity study of superconductivity in extended Hubbard models

NASA Astrophysics Data System (ADS)

Plonka, N.; Jia, C. J.; Wang, Y.; Moritz, B.; Devereaux, T. P.

2015-07-01

The Hubbard model with local on-site repulsion is generally thought to possess a superconducting ground state for appropriate parameters, but the effects of more realistic long-range Coulomb interactions have not been studied extensively. We study the influence of these interactions on superconductivity by including nearest- and next-nearest-neighbor extended Hubbard interactions in addition to the usual on-site terms. Utilizing numerical exact diagonalization, we analyze the signatures of superconductivity in the ground states through the fidelity metric of quantum information theory. We find that nearest and next-nearest neighbor interactions have thresholds above which they destabilize superconductivity regardless of whether they are attractive or repulsive, seemingly due to competing charge fluctuations.

An indoor positioning technology in the BLE mobile payment system

NASA Astrophysics Data System (ADS)

Han, Tiantian; Ding, Lei

2017-05-01

Mobile payment system for large supermarkets, the core function is through the BLE low-power Bluetooth technology to achieve the amount of payment in the mobile payment system, can through an indoor positioning technology to achieve value-added services. The technology by collecting Bluetooth RSSI, the fingerprint database of sampling points corresponding is established. To get Bluetooth module RSSI by the AP. Then, to use k-Nearest Neighbor match the value of the fingerprint database. Thereby, to help businesses find customers through the mall location, combined settlement amount of the customer's purchase of goods, to analyze customer's behavior. When the system collect signal strength, the distribution of the sampling points of RSSI is analyzed and the value is filtered. The system, used in the laboratory is designed to demonstrate the feasibility.

Are hospitals "keeping up with the Joneses"?: Assessing the spatial and temporal diffusion of the surgical robot.

PubMed

Li, Huilin; Gail, Mitchell H; Braithwaite, R Scott; Gold, Heather T; Walter, Dawn; Liu, Mengling; Gross, Cary P; Makarov, Danil V

2014-07-01

The surgical robot has been widely adopted in the United States in spite of its high cost and controversy surrounding its benefit. Some have suggested that a "medical arms race" influences technology adoption. We wanted to determine whether a hospital would acquire a surgical robot if its nearest neighboring hospital already owned one. We identified 554 hospitals performing radical prostatectomy from the Healthcare Cost and Utilization Project Statewide Inpatient Databases for seven states. We used publicly available data from the website of the surgical robot's sole manufacturer (Intuitive Surgical, Sunnyvale, CA) combined with data collected from the hospitals to ascertain the timing of robot acquisition during year 2001 to 2008. One hundred thirty four hospitals (24%) had acquired a surgical robot by the end of 2008. We geocoded the address of each hospital and determined a hospital's likelihood to acquire a surgical robot based on whether its nearest neighbor owned a surgical robot . We developed a Markov chain method to model the acquisition process spatially and temporally and quantified the "neighborhood effect" on the acquisition of the surgical robot while adjusting simultaneously for known confounders. After adjusting for hospital teaching status, surgical volume, urban status and number of hospital beds, the Markov chain analysis demonstrated that a hospital whose nearest neighbor had acquired a surgical robot had a higher likelihood itself acquiring a surgical robot. (OR=1.71, 95% CI: 1.07-2.72 , p=0.02). There is a significant spatial and temporal association for hospitals acquiring surgical robots during the study period. Hospitals were more likely to acquire a surgical robot during the robot's early adoption phase if their nearest neighbor had already done so.

An integrated classifier for computer-aided diagnosis of colorectal polyps based on random forest and location index strategies

NASA Astrophysics Data System (ADS)

Hu, Yifan; Han, Hao; Zhu, Wei; Li, Lihong; Pickhardt, Perry J.; Liang, Zhengrong

2016-03-01

Feature classification plays an important role in differentiation or computer-aided diagnosis (CADx) of suspicious lesions. As a widely used ensemble learning algorithm for classification, random forest (RF) has a distinguished performance for CADx. Our recent study has shown that the location index (LI), which is derived from the well-known kNN (k nearest neighbor) and wkNN (weighted k nearest neighbor) classifier [1], has also a distinguished role in the classification for CADx. Therefore, in this paper, based on the property that the LI will achieve a very high accuracy, we design an algorithm to integrate the LI into RF for improved or higher value of AUC (area under the curve of receiver operating characteristics -- ROC). Experiments were performed by the use of a database of 153 lesions (polyps), including 116 neoplastic lesions and 37 hyperplastic lesions, with comparison to the existing classifiers of RF and wkNN, respectively. A noticeable gain by the proposed integrated classifier was quantified by the AUC measure.

RRAM-based parallel computing architecture using k-nearest neighbor classification for pattern recognition

NASA Astrophysics Data System (ADS)

Jiang, Yuning; Kang, Jinfeng; Wang, Xinan

2017-03-01

Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.

Theoretical studies of the defect structures for the two Cr3+ centers in KCl

NASA Astrophysics Data System (ADS)

Liu, Xu-Sheng; Wu, Shao-Yi; Wu, Li-Na; Zhang, Li-Juan; Guo, Jia-Xing; Dong, Hui-Ning

2017-06-01

The spin Hamiltonian (SH) parameters (i.e. the zero-field splitting parameters (ZFSPs) and g factors) and local structures of the two Cr3+ centers I and II at room temperature in KCl single crystals are theoretically investigated from the perturbation calculations for a rhombically distorted octahedral 3d3 cluster. The impurity systems are attributed to the doped Cr(CN)63- groups into KCl replacing the host KCl65- ones, associated with two nearest neighbor potassium vacancies VK in [011] and [ 0 1 bar 1 bar ] axes in center I and one nearest neighbor VK along [ 0 1 bar 1 ] and another next-nearest neighbor VK along [100] axis in center II, respectively. In center I, the four coplanar and two axial ligands CN- undergo the shifts ∆R1 (≈0.0044 nm) away from the VK and ∆R2‧ (≈0.0144 nm) away from the central ion along Z axis, respectively, because of the electrostatic interactions. In center II, the impurity Cr3+ is found to undergo the shift ∆RC (≈0.0063 nm) towards the nearest neighbor VK along [ 0 1 bar 1 ] axis, while the two ligands in [001] and [ 0 1 bar 0 ] axes closest to the VK undergo the shifts ∆R1 (≈0.0081 nm) away from the respective VK, and the ligand intervening in the VK and the central ion experiences the shift ∆R2 (≈0.0238 nm) away from the VK along [100] axis. The charge-transfer (CT) contributions to g-shifts are found to be opposite in sign and more than half (characterized by the ratios |ΔgCT/ΔgCF|>50%) in magnitude compared with the CF ones for both centers. The local structures and the microscopic mechanisms of the relevant impurity and ligand shifts are discussed for the two centers.

Allele frequencies of 15 STR loci in Bosnian and Herzegovinian population

PubMed Central

Pilav, Amela; Pojskić, Naris; Ahatović, Anesa; Džehverović, Mirela; Čakar, Jasmina; Marjanović, Damir

2017-01-01

Aim To determine newest the most accurate allele frequencies for 15 short tandem repeat (STR) loci in the Bosnian and Herzegovinian population, calculate statistical parameters, and compare them with the relevant data for seven neighboring populations. Methods Genomic DNA was obtained from buccal swabs of 1000 unrelated individuals from all regions of Bosnia and Herzegovina. Genotyping was performed using PowerPlex® 16 System to obtain allele frequencies for 15 polymorphic STR loci including D3S1358, TH01, D21S11, D18S51, Penta E, D5S818, D13S317, D7S820, D16S539, CSF1PO, Penta D, vWA, D8S1179, TPOX, and FGA. The calculated allele frequencies were also compared with the data from neighboring populations. Results The highest detected value of polymorphism information content (PIC) was detected at the PentaE locus, whereas the lowest value was detected at the TPOX locus. The power of discrimination (PD) values had similar distribution, with Penta E showing the highest PD of 0.9788. While D18S51 had the highest value of power of exclusion (PE), the lowest PE value was detected at the TPOX locus. Conclusion Upon comparison of Bosnian and Herzegovinian population data with those of seven neighboring populations, the highest allele frequency differentiation was noticed between Bosnian and Herzegovinian and Turkish population at 5 loci, the most informative of which was Penta E. The neighbor-joining dendrogram constructed on the basis of genetic distance showed grouping of Slovenian, Austrian, Hungarian, and Croatian populations. Bosnian and Herzegovinian population was between the mentioned cluster and Serbian population. To determine more accurate distribution of allelic frequencies and forensic parameters, our study included 1000 unrelated individuals from all regions of Bosnia and Herzegovina, and our findings demonstrated the applicability of these markers in both forensics and future population genetic studies. PMID:28613042

Allele frequencies of 15 STR loci in Bosnian and Herzegovinian population.

PubMed

Pilav, Amela; Pojskić, Naris; Ahatović, Anesa; Džehverović, Mirela; Čakar, Jasmina; Marjanović, Damir

2017-06-14

To determine newest the most accurate allele frequencies for 15 short tandem repeat (STR) loci in the Bosnian and Herzegovinian population, calculate statistical parameters, and compare them with the relevant data for seven neighboring populations. Genomic DNA was obtained from buccal swabs of 1000 unrelated individuals from all regions of Bosnia and Herzegovina. Genotyping was performed using PowerPlex® 16 System to obtain allele frequencies for 15 polymorphic STR loci including D3S1358, TH01, D21S11, D18S51, Penta E, D5S818, D13S317, D7S820, D16S539, CSF1PO, Penta D, vWA, D8S1179, TPOX, and FGA. The calculated allele frequencies were also compared with the data from neighboring populations. The highest detected value of polymorphism information content (PIC) was detected at the PentaE locus, whereas the lowest value was detected at the TPOX locus. The power of discrimination (PD) values had similar distribution, with Penta E showing the highest PD of 0.9788. While D18S51 had the highest value of power of exclusion (PE), the lowest PE value was detected at the TPOX locus. Upon comparison of Bosnian and Herzegovinian population data with those of seven neighboring populations, the highest allele frequency differentiation was noticed between Bosnian and Herzegovinian and Turkish population at 5 loci, the most informative of which was Penta E. The neighbor-joining dendrogram constructed on the basis of genetic distance showed grouping of Slovenian, Austrian, Hungarian, and Croatian populations. Bosnian and Herzegovinian population was between the mentioned cluster and Serbian population. To determine more accurate distribution of allelic frequencies and forensic parameters, our study included 1000 unrelated individuals from all regions of Bosnia and Herzegovina, and our findings demonstrated the applicability of these markers in both forensics and future population genetic studies.

Role of dimensionality in Axelrod's model for the dissemination of culture

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-09-01

We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.

Local binary pattern texture-based classification of solid masses in ultrasound breast images

NASA Astrophysics Data System (ADS)

Matsumoto, Monica M. S.; Sehgal, Chandra M.; Udupa, Jayaram K.

2012-03-01

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

A regularization approach to hydrofacies delineation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wohlberg, Brendt; Tartakovsky, Daniel

2009-01-01

We consider an inverse problem of identifying complex internal structures of composite (geological) materials from sparse measurements of system parameters and system states. Two conceptual frameworks for identifying internal boundaries between constitutive materials in a composite are considered. A sequential approach relies on support vector machines, nearest neighbor classifiers, or geostatistics to reconstruct boundaries from measurements of system parameters and then uses system states data to refine the reconstruction. A joint approach inverts the two data sets simultaneously by employing a regularization approach.

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

Cooperation in N-person evolutionary snowdrift game in scale-free Barabási Albert networks

NASA Astrophysics Data System (ADS)

Lee, K. H.; Chan, Chun-Him; Hui, P. M.; Zheng, Da-Fang

2008-09-01

Cooperation in the N-person evolutionary snowdrift game (NESG) is studied in scale-free Barabási-Albert (BA) networks. Due to the inhomogeneity of the network, two versions of NESG are proposed and studied. In a model where the size of the competing group varies from agent to agent, the fraction of cooperators drops as a function of the payoff parameter. The networking effect is studied via the fraction of cooperative agents for nodes with a particular degree. For small payoff parameters, it is found that the small- k agents are dominantly cooperators, while large- k agents are of non-cooperators. Studying the spatial correlation reveals that cooperative agents will avoid to be nearest neighbors and the correlation disappears beyond the next-nearest neighbors. The behavior can be explained in terms of the networking effect and payoffs. In another model with a fixed size of competing groups, the fraction of cooperators could show a non-monotonic behavior in the regime of small payoff parameters. This non-trivial behavior is found to be a combined effect of the many agents with the smallest degree in the BA network and the increasing fraction of cooperators among these agents with the payoff for small payoffs.

Heterogeneity of allocation promotes cooperation in public goods games

NASA Astrophysics Data System (ADS)

Lei, Chuang; Wu, Te; Jia, Jian-Yuan; Cong, Rui; Wang, Long

2010-11-01

We investigate the effects of heterogeneous investment and distribution on the evolution of cooperation in the context of the public goods games. To do this, we develop a simple model in which each individual allocates differing funds to his direct neighbors based upon their difference in connectivity, because of the heterogeneity of real social ties. This difference is characterized by the weight of the link between paired individuals, with an adjustable parameter precisely controlling the heterogeneous level of ties. By numerical simulations, it is found that allocating both too much and too little funds to diverse neighbors can remarkably improve the cooperation level. However, there exists a worst mode of funds allocation leading to the most unfavorable cooperation induced by the moderate values of the parameter. In order to better reveal the potential causes behind these nontrivial phenomena we probe the microscopic characteristics including the average payoff and the cooperator density for individuals of different degrees. It demonstrates rather different dynamical behaviors between the modes of these two types of cooperation promoter. Besides, we also investigate the total link weights of individuals numerically and theoretically for negative values of the parameter, and conclude that the payoff magnitude of middle-degree nodes plays a crucial role in determining the cooperators’ fate.

Application of kernel functions for accurate similarity search in large chemical databases.

PubMed

Wang, Xiaohong; Huan, Jun; Smalter, Aaron; Lushington, Gerald H

2010-04-29

Similarity search in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases.

Fidelity study of superconductivity in extended Hubbard models

DOE PAGES

Plonka, N.; Jia, C. J.; Wang, Y.; ...

2015-07-08

The Hubbard model with local on-site repulsion is generally thought to possess a superconducting ground state for appropriate parameters, but the effects of more realistic long-range Coulomb interactions have not been studied extensively. We study the influence of these interactions on superconductivity by including nearest- and next-nearest-neighbor extended Hubbard interactions in addition to the usual on-site terms. Utilizing numerical exact diagonalization, we analyze the signatures of superconductivity in the ground states through the fidelity metric of quantum information theory. Finally, we find that nearest and next-nearest neighbor interactions have thresholds above which they destabilize superconductivity regardless of whether they aremore » attractive or repulsive, seemingly due to competing charge fluctuations.« less

The Effect of Quantum-Mechanical Interference on Precise Measurements of the n = 2 Triplet P Fine Structure of Helium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marsman, A.; Horbatsch, M.; Hessels, E. A., E-mail: hessels@yorku.ca

2015-09-15

For many decades, improvements in both theory and experiment of the fine structure of the n = 2 triplet P levels of helium have allowed for an increasingly precise determination of the fine-structure constant. Recently, it has been observed that quantum-mechanical interference between neighboring resonances can cause significant shifts, even if such neighboring resonances are separated by thousands of natural widths. The shifts depend in detail on the experimental method used for the measurement, as well as the specific experimental parameters employed. Here, we review how these shifts apply for the most precise measurements of the helium 2{sup 3}P fine-structuremore » intervals.« less

Optical components damage parameters database system

NASA Astrophysics Data System (ADS)

Tao, Yizheng; Li, Xinglan; Jin, Yuquan; Xie, Dongmei; Tang, Dingyong

2012-10-01

Optical component is the key to large-scale laser device developed by one of its load capacity is directly related to the device output capacity indicators, load capacity depends on many factors. Through the optical components will damage parameters database load capacity factors of various digital, information technology, for the load capacity of optical components to provide a scientific basis for data support; use of business processes and model-driven approach, the establishment of component damage parameter information model and database systems, system application results that meet the injury test optical components business processes and data management requirements of damage parameters, component parameters of flexible, configurable system is simple, easy to use, improve the efficiency of the optical component damage test.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

Magnetic Fields for All: The GPIPS Community Web-Access Portal

NASA Astrophysics Data System (ADS)

Carveth, Carol; Clemens, D. P.; Pinnick, A.; Pavel, M.; Jameson, K.; Taylor, B.

2007-12-01

The new GPIPS website portal provides community users with an intuitive and powerful interface to query the data products of the Galactic Plane Infrared Polarization Survey. The website, which was built using PHP for the front end and MySQL for the database back end, allows users to issue queries based on galactic or equatorial coordinates, GPIPS-specific identifiers, polarization information, magnitude information, and several other attributes. The returns are presented in HTML tables, with the added option of either downloading or being emailed an ASCII file including the same or more information from the database. Other functionalities of the website include providing details of the status of the Survey (which fields have been observed or are planned to be observed), techniques involved in data collection and analysis, and descriptions of the database contents and names. For this initial launch of the website, users may access the GPIPS polarization point source catalog and the deep coadd photometric point source catalog. Future planned developments include a graphics-based method for querying the database, as well as tools to combine neighboring GPIPS images into larger image files for both polarimetry and photometry. This work is partially supported by NSF grant AST-0607500.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatterjee, Anupam; Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076; Higham, Jonathan

A range of methods are presented to calculate a solute’s hydration shell from computer simulations of dilute solutions of monatomic ions and noble gas atoms. The methods are designed to be parameter-free and instantaneous so as to make them more general, accurate, and consequently applicable to disordered systems. One method is a modified nearest-neighbor method, another considers solute-water Lennard-Jones overlap followed by hydrogen-bond rearrangement, while three methods compare various combinations of water-solute and water-water forces. The methods are tested on a series of monatomic ions and solutes and compared with the values from cutoffs in the radial distribution function, themore » nearest-neighbor distribution functions, and the strongest-acceptor hydrogen bond definition for anions. The Lennard-Jones overlap method and one of the force-comparison methods are found to give a hydration shell for cations which is in reasonable agreement with that using a cutoff in the radial distribution function. Further modifications would be required, though, to make them capture the neighboring water molecules of noble-gas solutes if these weakly interacting molecules are considered to constitute the hydration shell.« less

Spin-1 Heisenberg ferromagnet using pair approximation method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mert, Murat; Mert, Gülistan; Kılıç, Ahmet

2016-06-08

Thermodynamic properties for Heisenberg ferromagnet with spin-1 on the simple cubic lattice have been calculated using pair approximation method. We introduce the single-ion anisotropy and the next-nearest-neighbor exchange interaction. We found that for negative single-ion anisotropy parameter, the internal energy is positive and heat capacity has two peaks.

A face and palmprint recognition approach based on discriminant DCT feature extraction.

PubMed

Jing, Xiao-Yuan; Zhang, David

2004-12-01

In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.

Novel utilization of the outer membrane proteins for the identification and differentiation of pathogenic versus nonpathogenic microbial strains using mass spectrometry-based proteomics approach

NASA Astrophysics Data System (ADS)

Jabbour, Rabih E.; Wade, Mary; Deshpande, Samir V.; McCubbin, Patrick; Snyder, A. Peter; Bevilacqua, Vicky

2012-06-01

Mass spectrometry based proteomic approaches are showing promising capabilities in addressing various biological and biochemical issues. Outer membrane proteins (OMPs) are often associated with virulence in gram-negative pathogens and could prove to be excellent model biomarkers for strain level differentiation among bacteria. Whole cells and OMP extracts were isolated from pathogenic and non-pathogenic strains of Francisella tularensis, Burkholderia thailandensis, and Burkholderia mallei. OMP extracts were compared for their ability to differentiate and delineate the correct database organism to an experimental sample and for the degree of dissimilarity to the nearest-neighbor database strains. This study addresses the comparative experimental proteome analyses of OMPs vs. whole cell lysates on the strain-level discrimination among gram negative pathogenic and non-pathogenic strains.

Extended Bose Hubbard model of interacting bosonic atoms in optical lattices: From superfluidity to density waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazzarella, G.; Giampaolo, S. M.; Illuminati, F.

2006-01-15

For systems of interacting, ultracold spin-zero neutral bosonic atoms, harmonically trapped and subject to an optical lattice potential, we derive an Extended Bose Hubbard (EBH) model by developing a systematic expansion for the Hamiltonian of the system in powers of the lattice parameters and of a scale parameter, the lattice attenuation factor. We identify the dominant terms that need to be retained in realistic experimental conditions, up to nearest-neighbor interactions and nearest-neighbor hoppings conditioned by the on-site occupation numbers. In the mean field approximation, we determine the free energy of the system and study the phase diagram both at zeromore » and at finite temperature. At variance with the standard on site Bose Hubbard model, the zero-temperature phase diagram of the EBH model possesses a dual structure in the Mott insulating regime. Namely, for specific ranges of the lattice parameters, a density wave phase characterizes the system at integer fillings, with domains of alternating mean occupation numbers that are the atomic counterparts of the domains of staggered magnetizations in an antiferromagnetic phase. We show as well that in the EBH model, a zero-temperature quantum phase transition to pair superfluidity is, in principle, possible, but completely suppressed at the lowest order in the lattice attenuation factor. Finally, we determine the possible occurrence of the different phases as a function of the experimentally controllable lattice parameters.« less

Contact processes with competitive dynamics in bipartite lattices: effects of distinct interactions

NASA Astrophysics Data System (ADS)

Pianegonda, Salete; Fiore, Carlos E.

2014-05-01

The two-dimensional contact process (CP) with a competitive dynamics proposed by Martins et al (2011 Phys. Rev. E 84 011125) leads to the appearance of an unusual active-asymmetric phase, in which the system sublattices are unequally populated. It differs from the usual CP only by the fact that particles also interact with their next-nearest neighbor sites via a distinct strength creation rate, and for the inclusion of an inhibition effect, proportional to the local density. Aimed at investigating the robustness of such an asymmetric phase, in this paper we study the influence of distinct interactions for two bidimensional CPs. In the first model, the interaction between first neighbors requires a minimal neighborhood of adjacent particles for creating new offspring, whereas second neighbors interact as usual (e.g. at least one neighboring particle is required). The second model takes the opposite situation, in which the restrictive dynamics is in the interaction between next-nearest neighbor sites. Both models are investigated under mean field theory (MFT) and Monte Carlo simulations. In similarity with results by Martins et al, the inclusion of distinct sublattice interactions maintains the occurrence of an asymmetric active phase and re-entrant transition lines. In contrast, remarkable differences are presented, such as discontinuous phase transitions (even between the active phases), the appearance of tricritical points and the stabilization of active phases under larger values of control parameters. Finally, we have shown that the critical behaviors are not altered due to the change of interactions, in which the absorbing transitions belong to the directed percolation (DP) universality class, whereas second-order active phase transitions belong to the Ising universality class.

Open Geoscience Database

NASA Astrophysics Data System (ADS)

Bashev, A.

2012-04-01

Currently there is an enormous amount of various geoscience databases. Unfortunately the only users of the majority of the databases are their elaborators. There are several reasons for that: incompaitability, specificity of tasks and objects and so on. However the main obstacles for wide usage of geoscience databases are complexity for elaborators and complication for users. The complexity of architecture leads to high costs that block the public access. The complication prevents users from understanding when and how to use the database. Only databases, associated with GoogleMaps don't have these drawbacks, but they could be hardly named "geoscience" Nevertheless, open and simple geoscience database is necessary at least for educational purposes (see our abstract for ESSI20/EOS12). We developed a database and web interface to work with them and now it is accessible at maps.sch192.ru. In this database a result is a value of a parameter (no matter which) in a station with a certain position, associated with metadata: the date when the result was obtained; the type of a station (lake, soil etc); the contributor that sent the result. Each contributor has its own profile, that allows to estimate the reliability of the data. The results can be represented on GoogleMaps space image as a point in a certain position, coloured according to the value of the parameter. There are default colour scales and each registered user can create the own scale. The results can be also extracted in *.csv file. For both types of representation one could select the data by date, object type, parameter type, area and contributor. The data are uploaded in *.csv format: Name of the station; Lattitude(dd.dddddd); Longitude(ddd.dddddd); Station type; Parameter type; Parameter value; Date(yyyy-mm-dd). The contributor is recognised while entering. This is the minimal set of features that is required to connect a value of a parameter with a position and see the results. All the complicated data treatment could be conducted in other programs after extraction the filtered data into *.csv file. It makes the database understandable for non-experts. The database employs open data format (*.csv) and wide spread tools: PHP as the program language, MySQL as database management system, JavaScript for interaction with GoogleMaps and JQueryUI for create user interface. The database is multilingual: there are association tables, which connect with elements of the database. In total the development required about 150 hours. The database still has several problems. The main problem is the reliability of the data. Actually it needs an expert system for estimation the reliability, but the elaboration of such a system would take more resources than the database itself. The second problem is the problem of stream selection - how to select the stations that are connected with each other (for example, belong to one water stream) and indicate their sequence. Currently the interface is English and Russian. However it can be easily translated to your language. But some problems we decided. For example problem "the problem of the same station" (sometimes the distance between stations is smaller, than the error of position): when you adding new station to the database our application automatically find station near this place. Also we decided problem of object and parameter type (how to regard "EC" and "electrical conductivity" as the same parameter). This problem has been solved using "associative tables". If you would like to see the interface on your language, just contact us. We should send you the list of terms and phrases for translation on your language. The main advantage of the database is that it is totally open: everybody can see, extract the data from the database and use them for non-commercial purposes with no charge. Registered users can contribute to the database without getting paid. We hope, that it will be widely used first of all for education purposes, but professional scientists could use it also.

Interactive Database of Pulsar Flux Density Measurements

NASA Astrophysics Data System (ADS)

Koralewska, O.; Krzeszowski, K.; Kijak, J.; Lewandowski, W.

2012-12-01

The number of astronomical observations is steadily growing, giving rise to the need of cataloguing the obtained results. There are a lot of databases, created to store different types of data and serve a variety of purposes, e. g. databases providing basic data for astronomical objects (SIMBAD Astronomical Database), databases devoted to one type of astronomical object (ATNF Pulsar Database) or to a set of values of the specific parameter (Lorimer 1995 - database of flux density measurements for 280 pulsars on the frequencies up to 1606 MHz), etc. We found that creating an online database of pulsar flux measurements, provided with facilities for plotting diagrams and histograms, calculating mean values for a chosen set of data, filtering parameter values and adding new measurements by the registered users, could be useful in further studies on pulsar spectra.

Evaluation of the separation characteristics of application-specific (volatile organic compounds) open-tubular columns for gas chromatography.

PubMed

Poole, Colin F; Qian, Jing; Kiridena, Waruna; Dekay, Colleen; Koziol, Wladyslaw W

2006-11-17

The solvation parameter model is used to characterize the separation characteristics of two application-specific open-tubular columns (Rtx-Volatiles and Rtx-VGC) and a general purpose column for the separation of volatile organic compounds (DB-WAXetr) at five equally spaced temperatures over the range 60-140 degrees C. System constant differences and retention factor correlation plots are then used to determine selectivity differences between the above columns and their closest neighbors in a large database of system constants and retention factors for forty-four open-tubular columns. The Rtx-Volatiles column is shown to have separation characteristics predicted for a poly(dimethyldiphenylsiloxane) stationary phase containing about 16% diphenylsiloxane monomer. The Rtx-VGC column has separation properties similar to the poly(cyanopropylphenyldimethylsiloxane) stationary phase containing 14% cyanopropylphenylsiloxane monomer DB-1701 for non-polar and dipolar/polarizable compounds but significantly different characteristics for the separation of hydrogen-bond acids. For all practical purposes the DB-WAXetr column is shown to be selectivity equivalent to poly(ethylene glycol) columns prepared using different chemistries for bonding and immobilizing the stationary phase. Principal component analysis and cluster analysis are then used to classify the system constants for the above columns and a sub-database of eleven open-tubular columns (DB-1, HP-5, DB-VRX, Rtx-20, DB-35, Rtx-50, Rtx-65, DB-1301, DB-1701, DB-200, and DB-624) commonly used for the separation of volatile organic compounds. A rationale basis for column selection based on differences in intermolecular interactions is presented as an aid to method development for the separation of volatile organic compounds.

The HITRAN 2008 Molecular Spectroscopic Database

NASA Technical Reports Server (NTRS)

Rothman, Laurence S.; Gordon, Iouli E.; Barbe, Alain; Benner, D. Chris; Bernath, Peter F.; Birk, Manfred; Boudon, V.; Brown, Linda R.; Campargue, Alain; Champion, J.-P.;

Heat-Energy Analysis for Solar Receivers

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1982-01-01

Heat-energy analysis program (HEAP) solves general heat-transfer problems, with some specific features that are "custom made" for analyzing solar receivers. Can be utilized not only to predict receiver performance under varying solar flux, ambient temperature and local heat-transfer rates but also to detect locations of hotspots and metallurgical difficulties and to predict performance sensitivity of neighboring component parameters.

Secreting and sensing the same molecule allows cells to achieve versatile social behaviors

PubMed Central

Youk, Hyun; Lim, Wendell A.

2014-01-01

Cells that secrete and sense the same signaling molecule are ubiquitous. To uncover the functional capabilities of the core ‘secrete-and-sense’ circuit motif shared by these cells, we engineered yeast to secrete and sense the mating pheromone. Perturbing each circuit element revealed parameters that control the degree to which the cell communicated with itself versus with its neighbors. This tunable interplay of self- and neighbor-communication enables cells to span a diverse repertoire of cellular behaviors. These include a cell being asocial by responding only to itself, social through quorum sensing and an isogenic population of cells splitting into social and asocial subpopulations. A mathematical model explained these behaviors. The versatility of the secrete-and-sense circuit motif may explain its recurrence across species. PMID:24503857

Tidal interactions in the expanding universe - The formation of prolate systems

NASA Technical Reports Server (NTRS)

Binney, J.; Silk, J.

1979-01-01

The study estimates the magnitude of the anisotropy that can be tidally induced in neighboring initially spherical protostructures, be they protogalaxies, protoclusters, or even uncollapsed density enhancements in the large-scale structure of the universe. It is shown that the linear analysis of tidal interactions developed by Peebles (1969) predicts that the anisotropy energy of a perturbation grows to first order in a small dimensionless parameter, whereas the net angular momentum acquired is of second order. A simple model is presented for the growth of anisotropy by tidal interactions during the nonlinear stage of the development of perturbations. A possible observational test is described of the alignment predicted by the model between the orientations of large-scale perturbations and the positions of neighboring density enhancements.

A binary linear programming formulation of the graph edit distance.

PubMed

Justice, Derek; Hero, Alfred

2006-08-01

A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs.

Chemical databases evaluated by order theoretical tools.

PubMed

Voigt, Kristina; Brüggemann, Rainer; Pudenz, Stefan

2004-10-01

Data on environmental chemicals are urgently needed to comply with the future chemicals policy in the European Union. The availability of data on parameters and chemicals can be evaluated by chemometrical and environmetrical methods. Different mathematical and statistical methods are taken into account in this paper. The emphasis is set on a new, discrete mathematical method called METEOR (method of evaluation by order theory). Application of the Hasse diagram technique (HDT) of the complete data-matrix comprising 12 objects (databases) x 27 attributes (parameters + chemicals) reveals that ECOTOX (ECO), environmental fate database (EFD) and extoxnet (EXT)--also called multi-database databases--are best. Most single databases which are specialised are found in a minimal position in the Hasse diagram; these are biocatalysis/biodegradation database (BID), pesticide database (PES) and UmweltInfo (UMW). The aggregation of environmental parameters and chemicals (equal weight) leads to a slimmer data-matrix on the attribute side. However, no significant differences are found in the "best" and "worst" objects. The whole approach indicates a rather bad situation in terms of the availability of data on existing chemicals and hence an alarming signal concerning the new and existing chemicals policies of the EEC.

The Finite-Size Scaling Relation for the Order-Parameter Probability Distribution of the Six-Dimensional Ising Model

NASA Astrophysics Data System (ADS)

Merdan, Ziya; Karakuş, Özlem

2016-11-01

The six dimensional Ising model with nearest-neighbor pair interactions has been simulated and verified numerically on the Creutz Cellular Automaton by using five bit demons near the infinite-lattice critical temperature with the linear dimensions L=4,6,8,10. The order parameter probability distribution for six dimensional Ising model has been calculated at the critical temperature. The constants of the analytical function have been estimated by fitting to probability function obtained numerically at the finite size critical point.

Superconductivity in the Penson-Kolb Model on a Triangular Lattice

NASA Astrophysics Data System (ADS)

Ptok, A.; Mierzejewski, M.

2008-07-01

We investigate properties of the two-dimensional Penson-Kolb model with repulsive pair hopping interaction. In the case of a bipartite square lattice this interaction may lead to the η-type pairing, when the phase of superconducting order parameter changes from one lattice site to the neighboring one. We show that this interaction may be responsible for the onset of superconductivity also for a triangular lattice. We discuss the spatial dependence of the superconducting order parameter and demonstrate that the total momentum of the paired electrons is determined by the lattice geometry.

DEPOT: A Database of Environmental Parameters, Organizations and Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

CARSON,SUSAN D.; HUNTER,REGINA LEE; MALCZYNSKI,LEONARD A.

2000-12-19

The Database of Environmental Parameters, Organizations, and Tools (DEPOT) has been developed by the Department of Energy (DOE) as a central warehouse for access to data essential for environmental risk assessment analyses. Initial efforts have concentrated on groundwater and vadose zone transport data and bioaccumulation factors. DEPOT seeks to provide a source of referenced data that, wherever possible, includes the level of uncertainty associated with these parameters. Based on the amount of data available for a particular parameter, uncertainty is expressed as a standard deviation or a distribution function. DEPOT also provides DOE site-specific performance assessment data, pathway-specific transport data,more » and links to environmental regulations, disposal site waste acceptance criteria, other environmental parameter databases, and environmental risk assessment models.« less

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

PubMed Central

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic. PMID:26177039

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.

PubMed

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Re-evaluation and updating of the seismic hazard of Lebanon

NASA Astrophysics Data System (ADS)

Huijer, Carla; Harajli, Mohamed; Sadek, Salah

2016-01-01

This paper presents the results of a study undertaken to evaluate the implications of the newly mapped offshore Mount Lebanon Thrust (MLT) fault system on the seismic hazard of Lebanon and the current seismic zoning and design parameters used by the local engineering community. This re-evaluation is critical, given that the MLT is located at close proximity to the major cities and economic centers of the country. The updated seismic hazard was assessed using probabilistic methods of analysis. The potential sources of seismic activities that affect Lebanon were integrated along with any/all newly established characteristics within an updated database which includes the newly mapped fault system. The earthquake recurrence relationships of these sources were developed from instrumental seismology data, historical records, and earlier studies undertaken to evaluate the seismic hazard of neighboring countries. Maps of peak ground acceleration contours, based on 10 % probability of exceedance in 50 years (as per Uniform Building Code (UBC) 1997), as well as 0.2 and 1 s peak spectral acceleration contours, based on 2 % probability of exceedance in 50 years (as per International Building Code (IBC) 2012), were also developed. Finally, spectral charts for the main coastal cities of Beirut, Tripoli, Jounieh, Byblos, Saida, and Tyre are provided for use by designers.

Modeling variability in dendritic ice crystal backscattering cross sections at millimeter wavelengths using a modified Rayleigh-Gans theory

NASA Astrophysics Data System (ADS)

Lu, Yinghui; Clothiaux, Eugene E.; Aydin, Kültegin; Botta, Giovanni; Verlinde, Johannes

2013-12-01

Using the Generalized Multi-particle Mie-method (GMM), Botta et al. (in this issue) [7] created a database of backscattering cross sections for 412 different ice crystal dendrites at X-, Ka- and W-band wavelengths for different incident angles. The Rayleigh-Gans theory, which accounts for interference effects but ignores interactions between different parts of an ice crystal, explains much, but not all, of the variability in the database of backscattering cross sections. Differences between it and the GMM range from -3.5 dB to +2.5 dB and are highly dependent on the incident angle. To explain the residual variability a physically intuitive iterative method was developed to estimate the internal electric field within an ice crystal that accounts for interactions between the neighboring regions within it. After modifying the Rayleigh-Gans theory using this estimated internal electric field, the difference between the estimated backscattering cross sections and those from the GMM method decreased to within 0.5 dB for most of the ice crystals. The largest percentage differences occur when the form factor from the Rayleigh-Gans theory is close to zero. Both interference effects and neighbor interactions are sensitive to the morphology of ice crystals. Improvements in ice-microphysical models are necessary to predict or diagnose internal structures within ice crystals to aid in more accurate interpretation of radar returns. Observations of the morphology of ice crystals are, in turn, necessary to guide the development of such ice-microphysical models and to better understand the statistical properties of ice crystal morphologies in different environmental conditions.

A novel method for the detection of R-peaks in ECG based on K-Nearest Neighbors and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

He, Runnan; Wang, Kuanquan; Li, Qince; Yuan, Yongfeng; Zhao, Na; Liu, Yang; Zhang, Henggui

2017-12-01

Cardiovascular diseases are associated with high morbidity and mortality. However, it is still a challenge to diagnose them accurately and efficiently. Electrocardiogram (ECG), a bioelectrical signal of the heart, provides crucial information about the dynamical functions of the heart, playing an important role in cardiac diagnosis. As the QRS complex in ECG is associated with ventricular depolarization, therefore, accurate QRS detection is vital for interpreting ECG features. In this paper, we proposed a real-time, accurate, and effective algorithm for QRS detection. In the algorithm, a proposed preprocessor with a band-pass filter was first applied to remove baseline wander and power-line interference from the signal. After denoising, a method combining K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) was used for accurate QRS detection in ECGs with different morphologies. The proposed algorithm was tested and validated using 48 ECG records from MIT-BIH arrhythmia database (MITDB), achieved a high averaged detection accuracy, sensitivity and positive predictivity of 99.43, 99.69, and 99.72%, respectively, indicating a notable improvement to extant algorithms as reported in literatures.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

PubMed

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Temperature threshold models for benthic macroinvertebrates in Idaho wadeable streams and neighboring ecoregions.

PubMed

Richards, David C; Lester, Gary; Pfeiffer, John; Pappani, Jason

2018-02-07

Water temperatures are warming throughout the world including the Pacific Northwest, USA. Benthic macroinvertebrates are one of the most important and widely used indicators of freshwater impairment; however, their response to increased water temperatures and their use for monitoring water temperature impairment has been hindered by lack of knowledge of temperature occurrences, threshold change points, or indicator taxa. We present new analysis of a large macroinvertebrate database provided by Idaho Department of Environmental Quality from wadeable streams in Idaho that is to be used in conjunction with our previous analyses. This new analysis provides threshold change points for over 400 taxa along an increasing temperature gradient and provides a list of statistically important indicator taxa. The macroinvertebrate assemblage temperature change point for the taxa that decreased with increased temperatures was determined to be about 20.5 °C and for the taxa assemblage that increased with increased temperatures was about 11.5 °C. Results of this new analysis combined with our previous analysis will also be useful for others in neighboring regions where these taxa occur.

Safety and Accuracy of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Identification of Highly Pathogenic Organisms.

PubMed

Rudrik, James T; Soehnlen, Marty K; Perry, Michael J; Sullivan, Maureen M; Reiter-Kintz, Wanda; Lee, Philip A; Pettit, Denise; Tran, Anthony; Swaney, Erin

2017-12-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) sample preparation methods, including the direct, on-plate formic acid, and ethanol/formic acid tube extraction methods, were evaluated for their ability to render highly pathogenic organisms nonviable and safe for handling in a biosafety level 2 laboratory. Of these, the tube extraction procedure was the most successful, with none of the tested strains surviving this sample preparation method. Tube extracts from several agents of bioterrorism and their near neighbors were analyzed in an eight-laboratory study to examine the utility of the Bruker Biotyper and Vitek MS MALDI-TOF MS systems and their in vitro diagnostic (IVD), research-use-only, and Security-Relevant databases, as applicable, to accurately identify these agents. Forty-six distinct strains of Bacillus anthracis , Yersinia pestis , Francisella tularensis , Burkholderia mallei , Burkholderia pseudomallei , Clostridium botulinum , Brucella melitensis , Brucella abortus , Brucella suis , and Brucella canis were extracted and distributed to participating laboratories for analysis. A total of 35 near-neighbor isolates were also analyzed. Copyright © 2017 Rudrik et al.

Lip reading using neural networks

NASA Astrophysics Data System (ADS)

Kalbande, Dhananjay; Mishra, Akassh A.; Patil, Sanjivani; Nirgudkar, Sneha; Patel, Prashant

2011-10-01

Computerized lip reading, or speech reading, is concerned with the difficult task of converting a video signal of a speaking person to written text. It has several applications like teaching deaf and dumb to speak and communicate effectively with the other people, its crime fighting potential and invariance to acoustic environment. We convert the video of the subject speaking vowels into images and then images are further selected manually for processing. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. Contour tracking methods and Template matching are used for the extraction of lips from the face. K Nearest Neighbor algorithm is then used to classify the 'speaking' images and the 'silent' images. The sequence of images is then transformed into segments of utterances. Feature vector is calculated on each frame for all the segments and is stored in the database with properly labeled class. Character recognition is performed using modified KNN algorithm which assigns more weight to nearer neighbors. This paper reports the recognition of vowels using KNN algorithms

Statistical organelle dissection of Arabidopsis guard cells using image database LIPS.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Hosokawa, Yoichiroh; Akita, Kae; Ebine, Kazuo; Ueda, Takashi; Kondo, Noriaki; Hasezawa, Seiichiro

2012-01-01

To comprehensively grasp cell biological events in plant stomatal movement, we have captured microscopic images of guard cells with various organelles markers. The 28,530 serial optical sections of 930 pairs of Arabidopsis guard cells have been released as a new image database, named Live Images of Plant Stomata (LIPS). We visualized the average organellar distributions in guard cells using probabilistic mapping and image clustering techniques. The results indicated that actin microfilaments and endoplasmic reticulum (ER) are mainly localized to the dorsal side and connection regions of guard cells. Subtractive images of open and closed stomata showed distribution changes in intracellular structures, including the ER, during stomatal movement. Time-lapse imaging showed that similar ER distribution changes occurred during stomatal opening induced by light irradiation or femtosecond laser shots on neighboring epidermal cells, indicating that our image analysis approach has identified a novel ER relocation in stomatal opening.

Reflective random indexing for semi-automatic indexing of the biomedical literature.

PubMed

Vasuki, Vidya; Cohen, Trevor

2010-10-01

The rapid growth of biomedical literature is evident in the increasing size of the MEDLINE research database. Medical Subject Headings (MeSH), a controlled set of keywords, are used to index all the citations contained in the database to facilitate search and retrieval. This volume of citations calls for efficient tools to assist indexers at the US National Library of Medicine (NLM). Currently, the Medical Text Indexer (MTI) system provides assistance by recommending MeSH terms based on the title and abstract of an article using a combination of distributional and vocabulary-based methods. In this paper, we evaluate a novel approach toward indexer assistance by using nearest neighbor classification in combination with Reflective Random Indexing (RRI), a scalable alternative to the established methods of distributional semantics. On a test set provided by the NLM, our approach significantly outperforms the MTI system, suggesting that the RRI approach would make a useful addition to the current methodologies.

Social inertia and diversity in collaboration networks

NASA Astrophysics Data System (ADS)

Ramasco, J. J.

2007-04-01

Random graphs are useful tools to study social interactions. In particular, the use of weighted random graphs allows to handle a high level of information concerning which agents interact and in which degree the interactions take place. Taking advantage of this representation, we recently defined a magnitude, the Social Inertia, that measures the eagerness of agents to keep ties with previous partners. To study this magnitude, we used collaboration networks that are specially appropriate to obtain valid statitical results due to the large size of publically available databases. In this work, I study the Social Inertia in two of these empirical networks, IMDB movie database and condmat. More specifically, I focus on how the Inertia relates to other properties of the graphs, and show that the Inertia provides information on how the weight of neighboring edges correlates. A social interpretation of this effect is also offered.

Quantum phase diagram of distorted J 1 - J 2 Heisenberg S  =  1/2 antiferromagnet in honeycomb lattice: a modified spin wave study

NASA Astrophysics Data System (ADS)

Ghorbani, Elaheh; Shahbazi, Farhad; Mosadeq, Hamid

2016-10-01

Using the modified spin wave method, we study the {{J}1}-{{J}2} Heisenberg model with first and second neighbor antiferromagnetic exchange interactions. For a symmetric S  =  1/2 model, with the same couplings for all the equivalent neighbors, we find three phases in terms of the frustration parameter \\barα={{J}2}/{{J}1} : (1) a commensurate collinear ordering with staggered magnetization (Néel.I state) for 0≤slant \\barα≲ 0.207 , (2) a magnetically gapped disordered state for 0.207≲ \\barα≲ 0.369 , preserving all the symmetries of the Hamiltonian and lattice, which by definition is a quantum spin liquid (QSL) state and (3) a commensurate collinear ordering in which two out of the three nearest neighbor magnetizations are antiparallel and the remaining pair are parallel (Néel.II state), for 0.396≲ \\barα≤slant 1 . We also explore the phase diagram of a distorted {{J}1}-{{J}2} model with S  =  1/2. Distortion is introduced as an inequality of one nearest neighbor coupling with the other two. This yields a richer phase diagram by the appearance of a new gapped QSL, a gapless QSL and also a valence bond crystal phase in addition to the previous three phases found for the undistorted model.

Band nesting, massive Dirac fermions, and valley Landé and Zeeman effects in transition metal dichalcogenides: A tight-binding model

NASA Astrophysics Data System (ADS)

Bieniek, Maciej; Korkusiński, Marek; Szulakowska, Ludmiła; Potasz, Paweł; Ozfidan, Isil; Hawrylak, Paweł

2018-02-01

We present here the minimal tight-binding model for a single layer of transition metal dichalcogenides (TMDCs) MX 2(M , metal; X , chalcogen) which illuminates the physics and captures band nesting, massive Dirac fermions, and valley Landé and Zeeman magnetic field effects. TMDCs share the hexagonal lattice with graphene but their electronic bands require much more complex atomic orbitals. Using symmetry arguments, a minimal basis consisting of three metal d orbitals and three chalcogen dimer p orbitals is constructed. The tunneling matrix elements between nearest-neighbor metal and chalcogen orbitals are explicitly derived at K ,-K , and Γ points of the Brillouin zone. The nearest-neighbor tunneling matrix elements connect specific metal and sulfur orbitals yielding an effective 6 ×6 Hamiltonian giving correct composition of metal and chalcogen orbitals but not the direct gap at K points. The direct gap at K , correct masses, and conduction band minima at Q points responsible for band nesting are obtained by inclusion of next-neighbor Mo-Mo tunneling. The parameters of the next-nearest-neighbor model are successfully fitted to MX 2(M =Mo ; X =S ) density functional ab initio calculations of the highest valence and lowest conduction band dispersion along K -Γ line in the Brillouin zone. The effective two-band massive Dirac Hamiltonian for MoS2, Landé g factors, and valley Zeeman splitting are obtained.

Quantum Correlation Properties in Composite Parity-Conserved Matrix Product States

NASA Astrophysics Data System (ADS)

Zhu, Jing-Min

2016-09-01

We give a new thought for constructing long-range quantum correlation in quantum many-body systems. Our proposed composite parity-conserved matrix product state has long-range quantum correlation only for two spin blocks where their spin-block length larger than 1 compared to any subsystem only having short-range quantum correlation, and we investigate quantum correlation properties of two spin blocks varying with environment parameter and spacing spin number. We also find that the geometry quantum discords of two nearest-neighbor spin blocks and two next-nearest-neighbor spin blocks become smaller and for other conditions the geometry quantum discord becomes larger than that in any subcomponent, i.e., the increase or the production of the long-range quantum correlation is at the cost of reducing the short-range quantum correlation compared to the corresponding classical correlation and total correlation having no any characteristic of regulation. For nearest-neighbor and next-nearest-neighbor all the correlations take their maximal values at the same points, while for other conditions no whether for spacing same spin number or for different spacing spin numbers all the correlations taking their maximal values are respectively at different points which are very close. We believe that our work is helpful to comprehensively and deeply understand the organization and structure of quantum correlation especially for long-range quantum correlation of quantum many-body systems; and further helpful for the classification, the depiction and the measure of quantum correlation of quantum many-body systems.

The coupling effects of kinematics and flexibility on the Lagrangian dynamic formulation of open chain deformable links

NASA Technical Reports Server (NTRS)

Changizi, Koorosh

1989-01-01

A nonlinear Lagrangian formulation for the spatial kinematic and dynamic analysis of open chain deformable links consisting of cylindrical joints that connect pairs of flexible links is developed. The special cases of revolute or prismatic joint can also be obtained from the kinematic equations. The kinematic equations are described using a 4x4 matrix method. The configuration of each deformable link in the open loop kinematic chain is identified using a coupled set of relative joint variables, constant geometric parameters, and elastic coordinates. The elastic coordinates define the link deformation with respect to a selected joint coordinate system that is consistent with the kinematic constraints on the boundary of the deformable link. These coordinates can be introduced using approximation techniques such as Rayleigh-Ritz method, finite element technique or any other desired approach. The large relative motion between two neighboring links are defined by a set of joint coordinates which describes the large relative translational and rotational motion between two neighboring joint coordinate systems. The origin of these coordinate systems are rigidly attached to the neighboring links at the joint definition points along the axis of motion.

An integrated metagenome and -proteome analysis of the microbial community residing in a biogas production plant.

PubMed

Ortseifen, Vera; Stolze, Yvonne; Maus, Irena; Sczyrba, Alexander; Bremges, Andreas; Albaum, Stefan P; Jaenicke, Sebastian; Fracowiak, Jochen; Pühler, Alfred; Schlüter, Andreas

2016-08-10

To study the metaproteome of a biogas-producing microbial community, fermentation samples were taken from an agricultural biogas plant for microbial cell and protein extraction and corresponding metagenome analyses. Based on metagenome sequence data, taxonomic community profiling was performed to elucidate the composition of bacterial and archaeal sub-communities. The community's cytosolic metaproteome was represented in a 2D-PAGE approach. Metaproteome databases for protein identification were compiled based on the assembled metagenome sequence dataset for the biogas plant analyzed and non-corresponding biogas metagenomes. Protein identification results revealed that the corresponding biogas protein database facilitated the highest identification rate followed by other biogas-specific databases, whereas common public databases yielded insufficient identification rates. Proteins of the biogas microbiome identified as highly abundant were assigned to the pathways involved in methanogenesis, transport and carbon metabolism. Moreover, the integrated metagenome/-proteome approach enabled the examination of genetic-context information for genes encoding identified proteins by studying neighboring genes on the corresponding contig. Exemplarily, this approach led to the identification of a Methanoculleus sp. contig encoding 16 methanogenesis-related gene products, three of which were also detected as abundant proteins within the community's metaproteome. Thus, metagenome contigs provide additional information on the genetic environment of identified abundant proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

MRPrimerV: a database of PCR primers for RNA virus detection

PubMed Central

Kim, Hyerin; Kang, NaNa; An, KyuHyeon; Kim, Doyun; Koo, JaeHyung; Kim, Min-Soo

2017-01-01

Many infectious diseases are caused by viral infections, and in particular by RNA viruses such as MERS, Ebola and Zika. To understand viral disease, detection and identification of these viruses are essential. Although PCR is widely used for rapid virus identification due to its low cost and high sensitivity and specificity, very few online database resources have compiled PCR primers for RNA viruses. To effectively detect viruses, the MRPrimerV database (http://MRPrimerV.com) contains 152 380 247 PCR primer pairs for detection of 1818 viruses, covering 7144 coding sequences (CDSs), representing 100% of the RNA viruses in the most up-to-date NCBI RefSeq database. Due to rigorous similarity testing against all human and viral sequences, every primer in MRPrimerV is highly target-specific. Because MRPrimerV ranks CDSs by the penalty scores of their best primer, users need only use the first primer pair for a single-phase PCR or the first two primer pairs for two-phase PCR. Moreover, MRPrimerV provides the list of genome neighbors that can be detected using each primer pair, covering 22 192 variants of 532 RefSeq RNA viruses. We believe that the public availability of MRPrimerV will facilitate viral metagenomics studies aimed at evaluating the variability of viruses, as well as other scientific tasks. PMID:27899620

Person Authentication Using Learned Parameters of Lifting Wavelet Filters

NASA Astrophysics Data System (ADS)

Niijima, Koichi

2006-10-01

This paper proposes a method for identifying persons by the use of the lifting wavelet parameters learned by kurtosis-minimization. Our learning method uses desirable properties of kurtosis and wavelet coefficients of a facial image. Exploiting these properties, the lifting parameters are trained so as to minimize the kurtosis of lifting wavelet coefficients computed for the facial image. Since this minimization problem is an ill-posed problem, it is solved by the aid of Tikhonov's regularization method. Our learning algorithm is applied to each of the faces to be identified to generate its feature vector whose components consist of the learned parameters. The constructed feature vectors are memorized together with the corresponding faces in a feature vectors database. Person authentication is performed by comparing the feature vector of a query face with those stored in the database. In numerical experiments, the lifting parameters are trained for each of the neutral faces of 132 persons (74 males and 58 females) in the AR face database. Person authentication is executed by using the smile and anger faces of the same persons in the database.

Strong competition between ΘI I-loop-current order and d -wave charge order along the diagonal direction in a two-dimensional hot spot model

NASA Astrophysics Data System (ADS)

de Carvalho, Vanuildo S.; Kloss, Thomas; Montiel, Xavier; Freire, Hermann; Pépin, Catherine

2015-08-01

We study the fate of the so-called ΘI I-loop-current order that breaks both time-reversal and parity symmetries in a two-dimensional hot spot model with antiferromagnetically mediated interactions, using Fermi surfaces relevant to the phenomenology of the cuprate superconductors. We start from a three-band Emery model describing the hopping of holes in the CuO2 plane that includes two hopping parameters tp p and tp d, local onsite Coulomb interactions Ud and Up, and nearest-neighbor Vp d couplings between the fermions in the copper [Cu (3 dx2-y2) ] and oxygen [O (2 px) and O (2 py)] orbitals. By focusing on the lowest-energy band, we proceed to decouple the local interaction Ud of the Cu orbital in the spin channel using a Hubbard-Stratonovich transformation to arrive at the interacting part of the so-called spin-fermion model. We also decouple the nearest-neighbor interaction Vp d to introduce the order parameter of the ΘI I-loop-current order. In this way, we are able to construct a consistent mean-field theory that describes the strong competition between the composite order parameter made of a quadrupole-density wave and d -wave pairing fluctuations proposed in Efetov et al. [Nat. Phys. 9, 442 (2013), 10.1038/nphys2641] with the ΘI I-loop-current order parameter that is argued to be relevant for explaining important aspects of the physics of the pseudogap phase displayed in the underdoped cuprates.

Non-Cooperative Target Imaging and Parameter Estimation with Narrowband Radar Echoes.

PubMed

Yeh, Chun-mao; Zhou, Wei; Lu, Yao-bing; Yang, Jian

2016-01-20

This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are formed on the velocity-acceleration plane at two neighboring coherent processing intervals (CPIs). Then, the rotating velocity (RV) is proposed to be estimated by utilizing the relationship between the positions of the scattering centers among two images. Finally, the target image is rescaled to the range-cross-range plane with the estimated rotational parameter. The validity of the proposed approach is confirmed using numerical simulations.

An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

ERIC Educational Resources Information Center

Pankau, Brian L.

2009-01-01

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.

PubMed

Mei, Gang; Xu, Nengxiong; Xu, Liangliang

2016-01-01

This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm.

Studying the hopping parameters of half-Heusler NaAuS using maximally localized Wannier function

NASA Astrophysics Data System (ADS)

Sihi, Antik; Lal, Sohan; Pandey, Sudhir K.

2018-04-01

Here, the electronic behavior of half-Heusler NaAuS is studied using PBEsol exchange correlation functional by plotting the band structure curve. These bands are reproduced using maximally localized Wannier function using WANNIER90. Tight-binding bands are nicely matched with density functional theory bands. By fitting the tight-binding model, hopping parameter for NaAuS is obtained by including Na 2s, 2p, Au 6s, 5p, 5d and S 3s, 3p orbitals within the energy interval of -5 to 16 eV around the Fermi level. In present study, hopping integrals for NaAuS are computed for the first primitive unit cell atoms as well as the first nearest neighbor primitive unit cell. The most dominating hopping integrals are found for Na (3s) - S (3s), Na (2px) - S (2px), Au (6s) - S (3px), Au (6s) - S (3py) and Au (6s) - S (3pz) orbitals. The hopping integrals for the first nearest neighbor primitive unit cell are also discussed in this manuscript. In future, these hopping integrals are very important to find the topological invariant for NaAuS compound.

Spatiotemporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-07-01

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog's inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable with respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.

Seismic hazard of American Samoa and neighboring South Pacific Islands--methods, data, parameters, and results

USGS Publications Warehouse

Petersen, Mark D.; Harmsen, Stephen C.; Rukstales, Kenneth S.; Mueller, Charles S.; McNamara, Daniel E.; Luco, Nicolas; Walling, Melanie

2012-01-01

American Samoa and the neighboring islands of the South Pacific lie near active tectonic-plate boundaries that host many large earthquakes which can result in strong earthquake shaking and tsunamis. To mitigate earthquake risks from future ground shaking, the Federal Emergency Management Agency requested that the U.S. Geological Survey prepare seismic hazard maps that can be applied in building-design criteria. This Open-File Report describes the data, methods, and parameters used to calculate the seismic shaking hazard as well as the output hazard maps, curves, and deaggregation (disaggregation) information needed for building design. Spectral acceleration hazard for 1 Hertz having a 2-percent probability of exceedance on a firm rock site condition (Vs30=760 meters per second) is 0.12 acceleration of gravity (1 second, 1 Hertz) and 0.32 acceleration of gravity (0.2 seconds, 5 Hertz) on American Samoa, 0.72 acceleration of gravity (1 Hertz) and 2.54 acceleration of gravity (5 Hertz) on Tonga, 0.15 acceleration of gravity (1 Hertz) and 0.55 acceleration of gravity (5 Hertz) on Fiji, and 0.89 acceleration of gravity (1 Hertz) and 2.77 acceleration of gravity (5 Hertz) on the Vanuatu Islands.

MO-A-BRD-09: A Data-Mining Algorithm for Large Scale Analysis of Dose-Outcome Relationships in a Database of Irradiated Head-And-Neck (HN) Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, SP; Quon, H; Kiess, AP

Purpose: To develop a framework for automatic extraction of clinically meaningful dosimetric-outcome relationships from an in-house, analytic oncology database. Methods: Dose-volume histograms (DVH) and clinical outcome-related structured data elements have been routinely stored to our database for 513 HN cancer patients treated from 2007 to 2014. SQL queries were developed to extract outcomes that had been assessed for at least 100 patients, as well as DVH curves for organs-at-risk (OAR) that were contoured for at least 100 patients. DVH curves for paired OAR (e.g., left and right parotids) were automatically combined and included as additional structures for analysis. For eachmore » OAR-outcome combination, DVH dose points, D(V{sub t}), at a series of normalized volume thresholds, V{sub t}=[0.01,0.99], were stratified into two groups based on outcomes after treatment completion. The probability, P[D(V{sub t})], of an outcome was modeled at each V{sub t} by logistic regression. Notable combinations, defined as having P[D(V{sub t})] increase by at least 5% per Gy (p<0.05), were further evaluated for clinical relevance using a custom graphical interface. Results: A total of 57 individual and combined structures and 115 outcomes were queried, resulting in over 6,500 combinations for analysis. Of these, 528 combinations met the 5%/Gy requirement, with further manual inspection revealing a number of reasonable models based on either reported literature or proximity between neighboring OAR. The data mining algorithm confirmed the following well-known toxicity/outcome relationships: dysphagia/larynx, voice changes/larynx, esophagitis/esophagus, xerostomia/combined parotids, and mucositis/oral mucosa. Other notable relationships included dysphagia/pharyngeal constrictors, nausea/brainstem, nausea/spinal cord, weight-loss/mandible, and weight-loss/combined parotids. Conclusion: Our database platform has enabled large-scale analysis of dose-outcome relationships. The current data-mining framework revealed both known and novel dosimetric and clinical relationships, underscoring the potential utility of this analytic approach. Multivariate models may be necessary to further evaluate the complex relationship between neighboring OARs and observed outcomes. This research was supported through collaborations with Elekta, Philips, and Toshiba.« less

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

NASA Technical Reports Server (NTRS)

Wang, Yi; Pant, Kapil; Brenner, Martin J.; Ouellette, Jeffrey A.

2018-01-01

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

California Fault Parameters for the National Seismic Hazard Maps and Working Group on California Earthquake Probabilities 2007

USGS Publications Warehouse

Wills, Chris J.; Weldon, Ray J.; Bryant, W.A.

2008-01-01

This report describes development of fault parameters for the 2007 update of the National Seismic Hazard Maps and the Working Group on California Earthquake Probabilities (WGCEP, 2007). These reference parameters are contained within a database intended to be a source of values for use by scientists interested in producing either seismic hazard or deformation models to better understand the current seismic hazards in California. These parameters include descriptions of the geometry and rates of movements of faults throughout the state. These values are intended to provide a starting point for development of more sophisticated deformation models which include known rates of movement on faults as well as geodetic measurements of crustal movement and the rates of movements of the tectonic plates. The values will be used in developing the next generation of the time-independent National Seismic Hazard Maps, and the time-dependant seismic hazard calculations being developed for the WGCEP. Due to the multiple uses of this information, development of these parameters has been coordinated between USGS, CGS and SCEC. SCEC provided the database development and editing tools, in consultation with USGS, Golden. This database has been implemented in Oracle and supports electronic access (e.g., for on-the-fly access). A GUI-based application has also been developed to aid in populating the database. Both the continually updated 'living' version of this database, as well as any locked-down official releases (e.g., used in a published model for calculating earthquake probabilities or seismic shaking hazards) are part of the USGS Quaternary Fault and Fold Database http://earthquake.usgs.gov/regional/qfaults/ . CGS has been primarily responsible for updating and editing of the fault parameters, with extensive input from USGS and SCEC scientists.

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

USGS Publications Warehouse

Wagener, T.; Hogue, T.; Schaake, J.; Duan, Q.; Gupta, H.; Andreassian, V.; Hall, A.; Leavesley, G.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

Medical Image Retrieval Using Multi-Texton Assignment.

PubMed

Tang, Qiling; Yang, Jirong; Xia, Xianfu

2018-02-01

In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation. We investigate the effects of different parameters on system performance in order to choose the appropriate ones for our datasets and carry out experiments on the IRMA-2009 medical collection and the mammographic patch dataset. The extensive experimental results demonstrate that the proposed method has superior performance.

Surface morphology of a modified ballistic deposition model.

PubMed

Banerjee, Kasturi; Shamanna, J; Ray, Subhankar

2014-08-01

The surface and bulk properties of a modified ballistic deposition model are investigated. The deposition rule interpolates between nearest- and next-nearest-neighbor ballistic deposition and the random deposition models. The stickiness of the depositing particle is controlled by a parameter and the type of interparticle force. Two such forces are considered: Coulomb and van der Waals type. The interface width shows three distinct growth regions before eventual saturation. The rate of growth depends more strongly on the stickiness parameter than on the type of interparticle force. However, the porosity of the deposits is strongly influenced by the interparticle force.

Controllability of the Coulomb charging energy in close-packed nanoparticle arrays.

PubMed

Duan, Chao; Wang, Ying; Sun, Jinling; Guan, Changrong; Grunder, Sergio; Mayor, Marcel; Peng, Lianmao; Liao, Jianhui

2013-11-07

We studied the electronic transport properties of metal nanoparticle arrays, particularly focused on the Coulomb charging energy. By comparison, we confirmed that it is more reasonable to estimate the Coulomb charging energy using the activation energy from the temperature-dependent zero-voltage conductance. Based on this, we systematically and comprehensively investigated the parameters that could be used to tune the Coulomb charging energy in nanoparticle arrays. We found that four parameters, including the particle core size, the inter-particle distance, the nearest neighboring number, and the dielectric constant of ligand molecules, could significantly tune the Coulomb charging energy.

A Framework for Cloudy Model Optimization and Database Storage

NASA Astrophysics Data System (ADS)

Calvén, Emilia; Helton, Andrew; Sankrit, Ravi

2018-01-01

We present a framework for producing Cloudy photoionization models of the nebular emission from novae ejecta and storing a subset of the results in SQL database format for later usage. The database can be searched for models best fitting observed spectral line ratios. Additionally, the framework includes an optimization feature that can be used in tandem with the database to search for and improve on models by creating new Cloudy models while, varying the parameters. The database search and optimization can be used to explore the structures of nebulae by deriving their properties from the best-fit models. The goal is to provide the community with a large database of Cloudy photoionization models, generated from parameters reflecting conditions within novae ejecta, that can be easily fitted to observed spectral lines; either by directly accessing the database using the framework code or by usage of a website specifically made for this purpose.

Assessment of Spatial Transferability of Process-Based Hydrological Model Parameters in Two Neighboring Catchments in the Himalayan Region

NASA Astrophysics Data System (ADS)

Nepal, S.

2016-12-01

The spatial transferability of the model parameters of the process-oriented distributed J2000 hydrological model was investigated in two glaciated sub-catchments of the Koshi river basin in eastern Nepal. The basins had a high degree of similarity with respect to their static landscape features. The model was first calibrated (1986-1991) and validated (1992-1997) in the Dudh Koshi sub-catchment. The calibrated and validated model parameters were then transferred to the nearby Tamor catchment (2001-2009). A sensitivity and uncertainty analysis was carried out for both sub-catchments to discover the sensitivity range of the parameters in the two catchments. The model represented the overall hydrograph well in both sub-catchments, including baseflow and medium range flows (rising and recession limbs). The efficiency results according to both Nash-Sutcliffe and the coefficient of determination was above 0.84 in both cases. The sensitivity analysis showed that the same parameter was most sensitive for Nash-Sutcliffe (ENS) and Log Nash-Sutcliffe (LNS) efficiencies in both catchments. However, there were some differences in sensitivity to ENS and LNS for moderate and low sensitive parameters, although the majority (13 out of 16 for ENS and 16 out of 16 for LNS) had a sensitivity response in a similar range. A generalized likelihood uncertainty estimation (GLUE) result suggest that most of the time the observed runoff is within the parameter uncertainty range, although occasionally the values lie outside the uncertainty range, especially during flood peaks and more in the Tamor. This may be due to the limited input data resulting from the small number of precipitation stations and lack of representative stations in high-altitude areas, as well as to model structural uncertainty. The results indicate that transfer of the J2000 parameters to a neighboring catchment in the Himalayan region with similar physiographic landscape characteristics is viable. This indicates the possibility of applying process-based J2000 model be to the ungauged catchments in the Himalayan region, which could provide important insights into the hydrological system dynamics and provide much needed information to support water resources planning and management.

Factors impacting sense of community among adults with brain injury.

PubMed

Ditchman, Nicole; Chan, Fong; Haak, Christopher; Easton, Amanda B

2017-05-01

Despite increasing interest in examining community outcomes following disability, sense of community (SOC) has received relatively no attention in the rehabilitation literature. SOC refers to feelings of belonging and attachment one has for a community and is of particular relevance for people with brain injury who are at increased risk of social isolation. The aim of this study was to investigate factors contributing to SOC for individuals with brain injury. Members from 2 brain injury associations (n = 98) participated in this survey-based study. Hierarchical regression analysis was used to explore demographic, disability-related, community and social participation variables' impact on SOC with regard to one's town or city. Follow-up mediation analyses were conducted to explore relationships among social self-efficacy, support network, neighboring behavior, and SOC. Findings indicated that disability-related and community variables accounted for over 40% of the variance in SOC. Size of social support network was the only significant independent contributor to SOC variance. Follow-up analyses provided support for (a) the partial mediating effect of social support network size on the relationship between social self-efficacy and SOC, and (b) the mediating effect of neighboring behavior on the relationship between social self-efficacy and social support network size. Findings from this study highlight the particular importance of self-efficacy, social support, and neighboring behaviors in promoting SOC for people with brain injury. Recommendations are provided to advance research efforts and inform intervention approaches to improve the felt experience of community among people with brain injury. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

BLAST and FASTA similarity searching for multiple sequence alignment.

PubMed

Pearson, William R

2014-01-01

BLAST, FASTA, and other similarity searching programs seek to identify homologous proteins and DNA sequences based on excess sequence similarity. If two sequences share much more similarity than expected by chance, the simplest explanation for the excess similarity is common ancestry-homology. The most effective similarity searches compare protein sequences, rather than DNA sequences, for sequences that encode proteins, and use expectation values, rather than percent identity, to infer homology. The BLAST and FASTA packages of sequence comparison programs provide programs for comparing protein and DNA sequences to protein databases (the most sensitive searches). Protein and translated-DNA comparisons to protein databases routinely allow evolutionary look back times from 1 to 2 billion years; DNA:DNA searches are 5-10-fold less sensitive. BLAST and FASTA can be run on popular web sites, but can also be downloaded and installed on local computers. With local installation, target databases can be customized for the sequence data being characterized. With today's very large protein databases, search sensitivity can also be improved by searching smaller comprehensive databases, for example, a complete protein set from an evolutionarily neighboring model organism. By default, BLAST and FASTA use scoring strategies target for distant evolutionary relationships; for comparisons involving short domains or queries, or searches that seek relatively close homologs (e.g. mouse-human), shallower scoring matrices will be more effective. Both BLAST and FASTA provide very accurate statistical estimates, which can be used to reliably identify protein sequences that diverged more than 2 billion years ago.

Towards a formal genealogical classification of the Lezgian languages (North Caucasus): testing various phylogenetic methods on lexical data.

PubMed

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies.

Towards a Formal Genealogical Classification of the Lezgian Languages (North Caucasus): Testing Various Phylogenetic Methods on Lexical Data

PubMed Central

Kassian, Alexei

2015-01-01

A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies. PMID:25719456

A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data

Treesearch

B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann

2012-01-01

The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ünlü, Hilmi, E-mail: hunlu@itu.edu.tr

We propose a non-orthogonal sp{sup 3} hybrid bond orbital model to determine the electronic properties of semiconductor heterostructures. The model considers the non-orthogonality of sp{sup 3} hybrid states of nearest neighboring adjacent atoms using the intra-atomic Coulomb interactions corrected Hartree-Fock atomic energies and metallic contribution to calculate the valence band width energies of group IV elemental and group III-V and II-VI compound semiconductors without any adjustable parameter.

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2012-01-01

This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.

Easy-to-use phylogenetic analysis system for hepatitis B virus infection.

PubMed

Sugiyama, Masaya; Inui, Ayano; Shin-I, Tadasu; Komatsu, Haruki; Mukaide, Motokazu; Masaki, Naohiko; Murata, Kazumoto; Ito, Kiyoaki; Nakanishi, Makoto; Fujisawa, Tomoo; Mizokami, Masashi

2011-10-01

  The molecular phylogenetic analysis has been broadly applied to clinical and virological study. However, the appropriate settings and application of calculation parameters are difficult for non-specialists of molecular genetics. In the present study, the phylogenetic analysis tool was developed for the easy determination of genotypes and transmission route.   A total of 23 patients of 10 families infected with hepatitis B virus (HBV) were enrolled and expected to undergo intrafamilial transmission. The extracted HBV DNA were amplified and sequenced in a region of the S gene.   The software to automatically classify query sequence was constructed and installed on the Hepatitis Virus Database (HVDB). Reference sequences were retrieved from HVDB, which contained major genotypes from A to H. Multiple-alignments using CLUSTAL W were performed before the genetic distance matrix was calculated with the six-parameter method. The phylogenetic tree was output by the neighbor-joining method. User interface using WWW-browser was also developed for intuitive control. This system was named as the easy-to-use phylogenetic analysis system (E-PAS). Twenty-three sera of 10 families were analyzed to evaluate E-PAS. The queries obtained from nine families were genotype C and were located in one cluster per family. However, one patient of a family was classified into the cluster different from her family, suggesting that E-PAS detected the sample distinct from that of her family on the transmission route.   The E-PAS to output phylogenetic tree was developed since requisite material was sequence data only. E-PAS could expand to determine HBV genotypes as well as transmission routes. © 2011 The Japan Society of Hepatology.

Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition.

PubMed

Carvajal, Gonzalo; Figueroa, Miguel

2014-07-01

Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Band-gap bowing and p-type doping of (Zn, Mg, Be)O wide-gap semiconductor alloys: a first-principles study

NASA Astrophysics Data System (ADS)

Shi, H.-L.; Duan, Y.

2008-12-01

Using a first-principles band-structure method and a special quasirandom structure (SQS) approach, we systematically calculate the band gap bowing parameters and p-type doping properties of (Zn, Mg, Be)O related random ternary and quaternary alloys. We show that the bowing parameters for ZnBeO and MgBeO alloys are large and dependent on composition. This is due to the size difference and chemical mismatch between Be and Zn(Mg) atoms. We also demonstrate that adding a small amount of Be into MgO reduces the band gap indicating that the bowing parameter is larger than the band-gap difference. We select an ideal N atom with lower p atomic energy level as dopant to perform p-type doping of ZnBeO and ZnMgBeO alloys. For N doped in ZnBeO alloy, we show that the acceptor transition energies become shallower as the number of the nearest neighbor Be atoms increases. This is thought to be because of the reduction of p- d repulsion. The NO acceptor transition energies are deep in the ZnMgBeO quaternary alloy lattice-matched to GaN substrate due to the lower valence band maximum. These decrease slightly as there are more nearest neighbor Mg atoms surrounding the N dopant. The important natural valence band alignment between ZnO, MgO, BeO, ZnBeO, and ZnMgBeO quaternary alloy is also investigated.

Heat conduction in diatomic chains with correlated disorder

NASA Astrophysics Data System (ADS)

Savin, Alexander V.; Zolotarevskiy, Vadim; Gendelman, Oleg V.

2017-01-01

The paper considers heat transport in diatomic one-dimensional lattices, containing equal amounts of particles with different masses. Ordering of the particles in the chain is governed by single correlation parameter - the probability for two neighboring particles to have the same mass. As this parameter grows from zero to unity, the structure of the chain varies from regular staggering chain to completely random configuration, and then - to very long clusters of particles with equal masses. Therefore, this correlation parameter allows a control of typical cluster size in the chain. In order to explore different regimes of the heat transport, two interatomic potentials are considered. The first one is an infinite potential wall, corresponding to instantaneous elastic collisions between the neighboring particles. In homogeneous chains such interaction leads to an anomalous heat transport. The other one is classical Lennard-Jones interatomic potential, which leads to a normal heat transport. The simulations demonstrate that the correlated disorder of the particle arrangement does not change the convergence properties of the heat conduction coefficient, but essentially modifies its value. For the collision potential, one observes essential growth of the coefficient for fixed chain length as the limit of large homogeneous clusters is approached. The thermal transport in these models remains superdiffusive. In the Lennard-Jones chain the effect of correlation appears to be not monotonous in the limit of low temperatures. This behavior stems from the competition between formation of long clusters mentioned above, and Anderson localization close to the staggering ordered state.

Analysis of Mycobacterium tuberculosis Genotypic Lineage Distribution in Chile and Neighboring Countries

PubMed Central

Lagos, Jaime; Couvin, David; Arata, Loredana; Tognarelli, Javier; Aguayo, Carolina; Leiva, Tamara; Arias, Fabiola; Hormazabal, Juan Carlos; Rastogi, Nalin; Fernández, Jorge

2016-01-01

Tuberculosis (TB), caused by the pathogen Mycobacterium tuberculosis (MTB), remains a disease of high importance to global public health. Studies into the population structure of MTB have become vital to monitoring possible outbreaks and also to develop strategies regarding disease control. Although Chile has a low incidence of MTB, the current rates of migration have the potential to change this scenario. We collected and analyzed a total of 458 M. tuberculosis isolates (1 isolate per patient) originating from all 15 regions of Chile. The isolates were genotyped using the spoligotyping method and the data obtained were analyzed and compared with the SITVIT2 database. A total of 169 different patterns were identified, of which, 119 patterns (408 strains) corresponded to Spoligotype International Types (SITs) and 50 patterns corresponded to orphan strains. The most abundantly represented SITs/lineages were: SIT53/T1 (11.57%), SIT33/LAM3 (9.6%), SIT42/LAM9 (9.39%), SIT50/H3 (5.9%), SIT37/T3 (5%); analysis of the spoligotyping minimum spanning tree as well as spoligoforest were suggestive of a recent expansion of SIT42, SIT50 and SIT37; all of which potentially evolved from SIT53. The most abundantly represented lineages were LAM (40.6%), T (34.1%) and Haarlem (13.5%). LAM was more prevalent in the Santiago (43.6%) and Concepción (44.1%) isolates, rather than the Iquique (29.4%) strains. The proportion of X lineage was appreciably higher in Iquique and Concepción (11.7% in both) as compared to Santiago (1.6%). Global analysis of MTB lineage distribution in Chile versus neighboring countries showed that evolutionary recent lineages (LAM, T and Haarlem) accounted together for 88.2% of isolates in Chile, a pattern which mirrored MTB lineage distribution in neighboring countries (n = 7378 isolates recorded in SITVIT2 database for Peru, Brazil, Paraguay, and Argentina; and published studies), highlighting epidemiological advantage of Euro-American lineages in this region. Finally, we also observed exclusive emergence of patterns SIT4014/X1 and SIT4015 (unknown lineage signature) that have hitherto been found exclusively in Chile, indicating that conditions specific to Chile, along with the unique genetic makeup of the Chilean population, might have allowed for a possible co-evolution leading to the success of these emerging genotypes. PMID:27518286

Survey on air pollution and cardiopulmonary mortality in shiraz from 2011 to 2012: an analytical-descriptive study.

PubMed

Dehghani, Mansooreh; Anushiravani, Amir; Hashemi, Hassan; Shamsedini, Narges

2014-06-01

Expanding cities with rapid economic development has resulted in increased energy consumption leading to numerous environmental problems for their residents. The aim of this study was to investigate the correlation between air pollution and mortality rate due to cardiovascular and respiratory diseases in Shiraz. This is an analytical cross-sectional study in which the correlation between major air pollutants (including carbon monoxide [CO], sulfur dioxide [SO2], nitrogen dioxide [NO2] and particle matter with a diameter of less than 10 μ [PM10]) and climatic parameters (temperature and relative humidity) with the number of those whom expired from cardiopulmonary disease in Shiraz from March 2011 to January 2012 was investigated. Data regarding the concentration of air pollutants were determined by Shiraz Environmental Organization. Information about climatic parameters was collected from the database of Iran's Meteorological Organization. The number of those expired from cardiopulmonary disease in Shiraz were provided by the Department of Health, Shiraz University of Medical Sciences. We used non-parametric correlation test to analyze the relationship between these parameters. The results demonstrated that in all the recorded data, the average monthly pollutants standard index (PSI) values of PM10 were higher than standard limits, while the average monthly PSI value of NO2 were lower than standard. There was no significant relationship between the number of those expired from cardiopulmonary disease and the air pollutant (P > 0.05). Air pollution can aggravate chronic cardiopulmonary disease. In the current study, one of the most important air pollutants in Shiraz was the PM10 component. Mechanical processes, such as wind blowing from neighboring countries, is the most important parameter increasing PM10 in Shiraz to alarming conditions. The average monthly variation in PSI values of air pollutants such as NO2, CO, and SO2 were lower than standard limits. Moreover, there was no significant correlation between the average monthly variation in PSI of NO2, CO, PM10, and SO2 and the number of those expired from cardiopulmonary disease in Shiraz.

Two new computational methods for universal DNA barcoding: a benchmark using barcode sequences of bacteria, archaea, animals, fungi, and land plants.

PubMed

Tanabe, Akifumi S; Toju, Hirokazu

2013-01-01

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used "1-nearest-neighbor" (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research.

The use of database management systems and artificial intelligence in automating the planning of optical navigation pictures

NASA Technical Reports Server (NTRS)

Davis, Robert P.; Underwood, Ian M.

1987-01-01

The use of database management systems (DBMS) and AI to minimize human involvement in the planning of optical navigation pictures for interplanetary space probes is discussed, with application to the Galileo mission. Parameters characterizing the desirability of candidate pictures, and the program generating them, are described. How these parameters automatically build picture records in a database, and the definition of the database structure, are then discussed. The various rules, priorities, and constraints used in selecting pictures are also described. An example is provided of an expert system, written in Prolog, for automatically performing the selection process.

Using a Standardized Clinical Quantitative Sensory Testing Battery to Judge the Clinical Relevance of Sensory Differences Between Adjacent Body Areas.

PubMed

Dimova, Violeta; Oertel, Bruno G; Lötsch, Jörn

2017-01-01

Skin sensitivity to sensory stimuli varies among different body areas. A standardized clinical quantitative sensory testing (QST) battery, established for the diagnosis of neuropathic pain, was used to assess whether the magnitude of differences between test sites reaches clinical significance. Ten different sensory QST measures derived from thermal and mechanical stimuli were obtained from 21 healthy volunteers (10 men) and used to create somatosensory profiles bilateral from the dorsum of the hands (the standard area for the assessment of normative values for the upper extremities as proposed by the German Research Network on Neuropathic Pain) and bilateral at volar forearms as a neighboring nonstandard area. The parameters obtained were statistically compared between test sites. Three of the 10 QST parameters differed significantly with respect to the "body area," that is, warmth detection, thermal sensory limen, and mechanical pain thresholds. After z-transformation and interpretation according to the QST battery's standard instructions, 22 abnormal values were obtained at the hand. Applying the same procedure to parameters assessed at the nonstandard site forearm, that is, z-transforming them to the reference values for the hand, 24 measurements values emerged as abnormal, which was not significantly different compared with the hand (P=0.4185). Sensory differences between neighboring body areas are statistically significant, reproducing prior knowledge. This has to be considered in scientific assessments where a small variation of the tested body areas may not be an option. However, the magnitude of these differences was below the difference in sensory parameters that is judged as abnormal, indicating a robustness of the QST instrument against protocol deviations with respect to the test area when using the method of comparison with a 95 % confidence interval of a reference dataset.

The Sznajd model with limited persuasion: competition between high-reputation and hesitant agents

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Murilo Castro de Oliveira, Paulo

2011-11-01

In this work we study a modified version of the two-dimensional Sznajd sociophysics model. In particular, we consider the effects of agents' reputations in the persuasion rules. In other words, a high-reputation group with a common opinion may convince its neighbors with probability p, which induces an increase of the group's reputation. On the other hand, there is always a probability q = 1 - p of the neighbors keeping their opinions, which induces a decrease of the group's reputation. These rules describe a competition between groups with high-reputation and hesitant agents, which makes the full-consensus states (with all spins pointing in one direction) more difficult to reach. As consequences, the usual phase transition does not occur for p < pc ~ 0.69 and the system presents realistic democracy-like situations, where the majority of spins are aligned in a certain direction, for a wide range of parameters.

Incommensurate phase of a triangular frustrated Heisenberg model studied via Schwinger-boson mean-field theory

NASA Astrophysics Data System (ADS)

Li, Peng; Su, Haibin; Dong, Hui-Ning; Shen, Shun-Qing

2009-08-01

We study a triangular frustrated antiferromagnetic Heisenberg model with nearest-neighbor interactions J1 and third-nearest-neighbor interactions J3 by means of Schwinger-boson mean-field theory. By setting an antiferromagnetic J3 and varying J1 from positive to negative values, we disclose the low-temperature features of its interesting incommensurate phase. The gapless dispersion of quasiparticles leads to the intrinsic T2 law of specific heat. The magnetic susceptibility is linear in temperature. The local magnetization is significantly reduced by quantum fluctuations. We address possible relevance of these results to the low-temperature properties of NiGa2S4. From a careful analysis of the incommensurate spin wavevector, the interaction parameters are estimated as J1≈-3.8755 K and J3≈14.0628 K, in order to account for the experimental data.

Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

PubMed

Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

2014-08-01

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

Emergence of cooperation with self-organized criticality

NASA Astrophysics Data System (ADS)

Park, Sangmin; Jeong, Hyeong-Chai

2012-02-01

Cooperation and self-organized criticality are two main keywords in current studies of evolution. We propose a generalized Bak-Sneppen model and provide a natural mechanism which accounts for both phenomena simultaneously. We use the prisoner's dilemma games to mimic the interactions among the members in the population. Each member is identified by its cooperation probability, and its fitness is given by the payoffs from neighbors. The least fit member with the minimum payoff is replaced by a new member with a random cooperation probability. When the neighbors of the least fit one are also replaced with a non-zero probability, a strong cooperation emerges. The Bak-Sneppen process builds a self-organized structure so that the cooperation can emerge even in the parameter region where a uniform or random population decreases the number of cooperators. The emergence of cooperation is due to the same dynamical correlation that leads to self-organized criticality in replacement activities.

Rb-NMR study of the quasi-one-dimensional competing spin-chain compound R b2C u2M o3O12

NASA Astrophysics Data System (ADS)

Matsui, Kazuki; Yagi, Ayato; Hoshino, Yukihiro; Atarashi, Sochiro; Hase, Masashi; Sasaki, Takahiko; Goto, Takayuki

2017-12-01

A Rb-NMR study has been performed on the quasi-one-dimensional competing spin chain R b2C u2M o3O12 with ferromagnetic and antiferromagnetic exchange interactions on nearest-neighboring and next-nearest neighboring spins, respectively. The system changes from a gapped ground state at zero field to a gapless state at HC≃2 T , where the existence of magnetic order below 1 K was demonstrated by a broadening of the NMR spectrum, associated with a critical divergence of 1 /T1 . In the higher-temperature region, T1-1 showed a power-law-type temperature dependence, from which the field dependence of the Luttinger parameter K was obtained and compared with theoretical calculations based on the spin nematic Tomonaga-Luttinger liquid (TLL) state.

Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Liu, Yuanming; Huang, Changwei; Dai, Qionglin

2018-06-01

Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

NASA Astrophysics Data System (ADS)

Nababan, A. A.; Sitompul, O. S.; Tulus

2018-04-01

K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models.

PubMed

Bilgili, Mehmet; Sahin, Besir; Sangun, Levent

2013-01-01

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.

Trends in external causes of child and adolescent mortality in Poland, 1999-2012.

PubMed

Grajda, Aneta; Kułaga, Zbigniew; Gurzkowska, Beata; Góźdź, Magdalena; Wojtyło, Małgorzata; Litwin, Mieczysław

2017-01-01

To examine the pattern and trend of deaths due to external causes among Polish children and adolescents in 1999-2012, and to compare trends in Poland's neighboring countries. Death records were obtained from the Central Statistical Office of Poland. External causes mortality rates (MR) with 95 % confidence interval were calculated. The annual percentage change of MR was examined using linear regression. To compare MR with Belarus, Ukraine, Czech Republic and Germany, data from the European Mortality Database were used. MR were the highest in the age 15-19 years (33.7/100,000) and among boys (22.7/100,000). Unintentional injuries including transport accidents, drowning, and suicides (especially in children over 10 years old), were the main cause of death in the analyzed groups. Between 1999 and 2012 annual MR for unintentional injuries declined substantially. MR due to injuries and poisoning in Poland were higher compared with Czech Republic and Germany and lower in comparison with Belarus and Ukraine. Deaths due to unintentional injuries are still the leading cause of death among Polish children and adolescents. There are differences in death rates between Poland and neighboring countries.

Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile.

PubMed

van Laarhoven, Twan; Marchiori, Elena

2013-01-01

In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction. Drug-target interaction data are available for many classes of pharmaceutically useful target proteins including enzymes, ion channels, GPCRs and nuclear receptors. However, current drug-target interaction databases contain a small number of drug-target pairs which are experimentally validated interactions. In particular, for some drug compounds (or targets) there is no available interaction. This motivates the need for developing methods that predict interacting pairs with high accuracy also for these 'new' drug compounds (or targets). We show that a simple weighted nearest neighbor procedure is highly effective for this task. We integrate this procedure into a recent machine learning method for drug-target interaction we developed in previous work. Results of experiments indicate that the resulting method predicts true interactions with high accuracy also for new drug compounds and achieves results comparable or better than those of recent state-of-the-art algorithms. Software is publicly available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2013/.

A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

NASA Astrophysics Data System (ADS)

Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

2005-05-01

Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

Analysis of forensically used autosomal short tandem repeat markers in Polish and neighboring populations.

PubMed

Soltyszewski, Ireneusz; Plocienniczak, Andrzej; Fabricius, Hans Ake; Kornienko, Igor; Vodolazhsky, Dmitrij; Parson, Walther; Hradil, Roman; Schmitter, Hermann; Ivanov, Pavel; Kuzniar, Piotr; Malyarchuk, Boris A; Grzybowski, Tomasz; Woźniak, Marcin; Henke, Jurgen; Henke, Lotte; Olkhovets, Sergiv; Voitenko, Vladimir; Lagus, Vita; Ficek, Andrej; Minárik, Gabriel; de Knijff, Peter; Rebała, Krzysztof; Wysocka, Joanna; Kapińska, Ewa; Cybulska, Lidia; Mikulich, Alexei I; Tsybovsky, Iosif S; Szczerkowska, Zofia; Krajewski, Paweł; Ploski, Rafał

2008-06-01

The purpose of this study was to evaluate the homogeneity of Polish populations with respect to STRs chosen as core markers of the Polish Forensic National DNA Intelligence Database, and to provide reference allele frequencies and to explore the genetic interrelationship between Poland and neighboring countries. The allele frequency distribution of 10 STRs included in the SGMplus kit was analyzed among 2176 unrelated individuals from 6 regional Polish populations and among 4321 individuals from Germany (three samples), Austria, The Netherlands, Sweden, Czech Republic, Slovakia, Belarus, Ukraine and the Russian Federation (six samples). The statistical approach consisted of AMOVA, calculation of pairwise Rst values and analysis by multidimensional scaling. We found homogeneity of present day Poland and consistent differences between Polish and German populations which contrasted with relative similarities between Russian and German populations. These discrepancies between genetic and geographic distances were confirmed by analysis of an independent data set on Y chromosome STRs. Migrations of Goths, Viking influences, German settlements in the region of Volga river and/or forced population resettlements and other events related to World War II are the historic events which might have caused these finding.

Physiological Information Database (PID)

EPA Science Inventory

EPA has developed a physiological information database (created using Microsoft ACCESS) intended to be used in PBPK modeling. The database contains physiological parameter values for humans from early childhood through senescence as well as similar data for laboratory animal spec...

A Knowledge Database on Thermal Control in Manufacturing Processes

NASA Astrophysics Data System (ADS)

Hirasawa, Shigeki; Satoh, Isao

A prototype version of a knowledge database on thermal control in manufacturing processes, specifically, molding, semiconductor manufacturing, and micro-scale manufacturing has been developed. The knowledge database has search functions for technical data, evaluated benchmark data, academic papers, and patents. The database also displays trends and future roadmaps for research topics. It has quick-calculation functions for basic design. This paper summarizes present research topics and future research on thermal control in manufacturing engineering to collate the information to the knowledge database. In the molding process, the initial mold and melt temperatures are very important parameters. In addition, thermal control is related to many semiconductor processes, and the main parameter is temperature variation in wafers. Accurate in-situ temperature measurment of wafers is important. And many technologies are being developed to manufacture micro-structures. Accordingly, the knowledge database will help further advance these technologies.

Database constraints applied to metabolic pathway reconstruction tools.

PubMed

Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

2014-01-01

Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

Validated environmental and physiological data from the CELSS Breadboard Projects Biomass Production Chamber. BWT931 (Wheat cv. Yecora Rojo)

NASA Technical Reports Server (NTRS)

Stutte, G. W.; Mackowiak, C. L.; Markwell, G. A.; Wheeler, R. M.; Sager, J. C.

1993-01-01

This KSC database is being made available to the scientific research community to facilitate the development of crop development models, to test monitoring and control strategies, and to identify environmental limitations in crop production systems. The KSC validated dataset consists of 17 parameters necessary to maintain bioregenerative life support functions: water purification, CO2 removal, O2 production, and biomass production. The data are available on disk as either a DATABASE SUBSET (one week of 5-minute data) or DATABASE SUMMARY (daily averages of parameters). Online access to the VALIDATED DATABASE will be made available to institutions with specific programmatic requirements. Availability and access to the KSC validated database are subject to approval and limitations implicit in KSC computer security policies.

A lattice model for influenza spreading.

PubMed

Liccardo, Antonella; Fierro, Annalisa

2013-01-01

We construct a stochastic SIR model for influenza spreading on a D-dimensional lattice, which represents the dynamic contact network of individuals. An age distributed population is placed on the lattice and moves on it. The displacement from a site to a nearest neighbor empty site, allows individuals to change the number and identities of their contacts. The dynamics on the lattice is governed by an attractive interaction between individuals belonging to the same age-class. The parameters, which regulate the pattern dynamics, are fixed fitting the data on the age-dependent daily contact numbers, furnished by the Polymod survey. A simple SIR transmission model with a nearest neighbors interaction and some very basic adaptive mobility restrictions complete the model. The model is validated against the age-distributed Italian epidemiological data for the influenza A(H1N1) during the [Formula: see text] season, with sensible predictions for the epidemiological parameters. For an appropriate topology of the lattice, we find that, whenever the accordance between the contact patterns of the model and the Polymod data is satisfactory, there is a good agreement between the numerical and the experimental epidemiological data. This result shows how rich is the information encoded in the average contact patterns of individuals, with respect to the analysis of the epidemic spreading of an infectious disease.

The role of persuasion power on the consensus formation

NASA Astrophysics Data System (ADS)

Gündüç, Semra; Eryiğit, Recep

2015-05-01

An opinion dynamics model which is based on a version of two dimensional Sznajd model is introduced. According to this model the dynamics is governed by the interactions between four agents which live on the corners of a plaquette and their neighbors. The distinctive feature of the model is that each individual is identified by two parameters, namely, opinion and persuasion ability. The united group may persuade the individuals living at the neighboring sites according to both the number and their persuasion ability. This form of the model is used to discuss opinion dynamics processes in societies where a campaign is conducted by the principle being united and putting forward arguments which are commonly accepted by the members of the society. It is seen that persuasion parameter plays the major role in the societies where a minority opinion gains ground to be the major opinion of the society. The model has been applied to the Scottish referendum opinion poles data since 2011. The model in its simplicity, predicts that the arguments of the minority opinion ("YES" votes) are more appealing despite the observed win of the "NO" votes. This result may be due to the abundance of the "NO" opinion supporters at the beginning of the campaign.

Investigation of the Flow Structure on a Flat Plate Induced by Unsteady Plasma Actuation with DNS Methods

NASA Astrophysics Data System (ADS)

Yu, Jianyang; Chen, Fu; Liu, Huaping; Song, Yanping

2015-12-01

An investigation into the flow characteristic on a flat plate induced by an unsteady plasma was conducted with the methods of direct numerical simulations (DNS). A simplified model of dielectric barrier discharge (DBD) plasma was applied and its parameters were calibrated with the experimental results. In the simulations, effects of the actuation frequency on the flow were examined. The instantaneous flow parameters were also drawn to serve as a detailed study on the behavior when the plasma actuator was applied to the flow. The result shows that induced by the unsteady actuation, a series of vortex pairs which showed dipole formation and periodicity distribution were formed in the boundary layer. The production of these vortex pairs indicated a strong energy exchange between the main flow and the boundary layer. They moved downstream under the action of the free stream and decayed under the influence of the fluid viscosity. The distance of the neighboring vortices was found to be determined by the actuation frequency. Interaction of the neighboring vortices would be ignored when the actuation frequency was too small to make a difference. supported by the Foundation for Innovative Research Groups of National Natural Science Foundation of China (No. 51121004) and National Natural Science Foundation of China (No. 50976026)

Full magnetic dispersion relation in the frustrated quasi-1D ferromagnet Ca2Y2Cu5O10

NASA Astrophysics Data System (ADS)

Matsuda, M.; Ma, J.; Garlea, V. O.; Nishimoto, S.; Drechsler, S.-L.; Kuzian, R. O.; Ito, T.; Yamaguchi, H.; Oka, K.

2014-03-01

Ca2Y2Cu5O10 consists of edge-sharing CuO2 chains, in which Cu2+ ions carry spin 1/2. The nearest-neighbor (J1) and the next-nearest-neighbor interaction (J2) are ferromagnetic and antiferromagnetic, respectively. For the J1-J2 model the theory predicts that when the ratio α(= | J2 /J1 |) becomes larger than 0.25, the ground state becomes a spiral state. For the aforementioned compound, Kuzian et al. determined α to be 0.19, which is close to the critical value. However, the parameters were fitted using the observed data up to ~10 meV, above which the magnetic excitations were found to be broadened. In order to determine the overall dispersion relation, we performed inelastic neutron scattering experiments using the HYSPEC neutron spectrometer at the SNS. We succeeded in observing the full magnetic dispersion that extends up to ~55 meV. As previously observed, the magnetic excitations appeared to almost vanish at ~11.5 meV. We also found another noticeable gap-like behavior at ~28 meV. We re-evaluate the essential exchange coupling parameters and discuss the origin of gap-like regions in the spin-wave dispersion.

Explaining scene composition using kinematic chains of humans: application to Portuguese tiles history

NASA Astrophysics Data System (ADS)

da Silva, Nuno Pinho; Marques, Manuel; Carneiro, Gustavo; Costeira, João P.

2011-03-01

Painted tile panels (Azulejos) are one of the most representative Portuguese forms of art. Most of these panels are inspired on, and sometimes are literal copies of, famous paintings, or prints of those paintings. In order to study the Azulejos, art historians need to trace these roots. To do that they manually search art image databases, looking for images similar to the representation on the tile panel. This is an overwhelming task that should be automated as much as possible. Among several cues, the pose of humans and the general composition of people in a scene is quite discriminative. We build an image descriptor, combining the kinematic chain of each character, and contextual information about their composition, in the scene. Given a query image, our system computes its similarity profile over the database. Using nearest neighbors in the space of the descriptors, the proposed system retrieves the prints that most likely inspired the tiles' work.

Unsupervised Indoor Localization Based on Smartphone Sensors, iBeacon and Wi-Fi.

PubMed

Chen, Jing; Zhang, Yi; Xue, Wei

2018-04-28

In this paper, we propose UILoc, an unsupervised indoor localization scheme that uses a combination of smartphone sensors, iBeacons and Wi-Fi fingerprints for reliable and accurate indoor localization with zero labor cost. Firstly, compared with the fingerprint-based method, the UILoc system can build a fingerprint database automatically without any site survey and the database will be applied in the fingerprint localization algorithm. Secondly, since the initial position is vital to the system, UILoc will provide the basic location estimation through the pedestrian dead reckoning (PDR) method. To provide accurate initial localization, this paper proposes an initial localization module, a weighted fusion algorithm combined with a k-nearest neighbors (KNN) algorithm and a least squares algorithm. In UILoc, we have also designed a reliable model to reduce the landmark correction error. Experimental results show that the UILoc can provide accurate positioning, the average localization error is about 1.1 m in the steady state, and the maximum error is 2.77 m.

Online Mendelian Inheritance in Man (OMIM).

PubMed

Hamosh, A; Scott, A F; Amberger, J; Valle, D; McKusick, V A

2000-01-01

Online Mendelian Inheritance In Man (OMIM) is a public database of bibliographic information about human genes and genetic disorders. Begun by Dr. Victor McKusick as the authoritative reference Mendelian Inheritance in Man, it is now distributed electronically by the National Center for Biotechnology Information (NCBI). Material in OMIM is derived from the biomedical literature and is written by Dr. McKusick and his colleagues at Johns Hopkins University and elsewhere. Each OMIM entry has a full text summary of a genetic phenotype and/or gene and has copious links to other genetic resources such as DNA and protein sequence, PubMed references, mutation databases, approved gene nomenclature, and more. In addition, NCBI's neighboring feature allows users to identify related articles from PubMed selected on the basis of key words in the OMIM entry. Through its many features, OMIM is increasingly becoming a major gateway for clinicians, students, and basic researchers to the ever-growing literature and resources of human genetics. Copyright 2000 Wiley-Liss, Inc.

CAVIAR: CLASSIFICATION VIA AGGREGATED REGRESSION AND ITS APPLICATION IN CLASSIFYING OASIS BRAIN DATABASE

PubMed Central

Chen, Ting; Rangarajan, Anand; Vemuri, Baba C.

2010-01-01

This paper presents a novel classification via aggregated regression algorithm – dubbed CAVIAR – and its application to the OASIS MRI brain image database. The CAVIAR algorithm simultaneously combines a set of weak learners based on the assumption that the weight combination for the final strong hypothesis in CAVIAR depends on both the weak learners and the training data. A regularization scheme using the nearest neighbor method is imposed in the testing stage to avoid overfitting. A closed form solution to the cost function is derived for this algorithm. We use a novel feature – the histogram of the deformation field between the MRI brain scan and the atlas which captures the structural changes in the scan with respect to the atlas brain – and this allows us to automatically discriminate between various classes within OASIS [1] using CAVIAR. We empirically show that CAVIAR significantly increases the performance of the weak classifiers by showcasing the performance of our technique on OASIS. PMID:21151847

CAVIAR: CLASSIFICATION VIA AGGREGATED REGRESSION AND ITS APPLICATION IN CLASSIFYING OASIS BRAIN DATABASE.

PubMed

Chen, Ting; Rangarajan, Anand; Vemuri, Baba C

2010-04-14

This paper presents a novel classification via aggregated regression algorithm - dubbed CAVIAR - and its application to the OASIS MRI brain image database. The CAVIAR algorithm simultaneously combines a set of weak learners based on the assumption that the weight combination for the final strong hypothesis in CAVIAR depends on both the weak learners and the training data. A regularization scheme using the nearest neighbor method is imposed in the testing stage to avoid overfitting. A closed form solution to the cost function is derived for this algorithm. We use a novel feature - the histogram of the deformation field between the MRI brain scan and the atlas which captures the structural changes in the scan with respect to the atlas brain - and this allows us to automatically discriminate between various classes within OASIS [1] using CAVIAR. We empirically show that CAVIAR significantly increases the performance of the weak classifiers by showcasing the performance of our technique on OASIS.

MatProps: Material Properties Database and Associated Access Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durrenberger, J K; Becker, R C; Goto, D M

2007-08-13

Coefficients for analytic constitutive and equation of state models (EOS), which are used by many hydro codes at LLNL, are currently stored in a legacy material database (Steinberg, UCRL-MA-106349). Parameters for numerous materials are available through this database, and include Steinberg-Guinan and Steinberg-Lund constitutive models for metals, JWL equations of state for high explosives, and Mie-Gruniesen equations of state for metals. These constitutive models are used in most of the simulations done by ASC codes today at Livermore. Analytic EOSs are also still used, but have been superseded in many cases by tabular representations in LEOS (http://leos.llnl.gov). Numerous advanced constitutivemore » models have been developed and implemented into ASC codes over the past 20 years. These newer models have more physics and better representations of material strength properties than their predecessors, and therefore more model coefficients. However, a material database of these coefficients is not readily available. Therefore incorporating these coefficients with those of the legacy models into a portable database that could be shared amongst codes would be most welcome. The goal of this paper is to describe the MatProp effort at LLNL to create such a database and associated access library that could be used by codes throughout the DOE complex and beyond. We have written an initial version of the MatProp database and access library and our DOE/ASC code ALE3D (Nichols et. al., UCRL-MA-152204) is able to import information from the database. The database, a link to which exists on the Sourceforge server at LLNL, contains coefficients for many materials and models (see Appendix), and includes material parameters in the following categories--flow stress, shear modulus, strength, damage, and equation of state. Future versions of the Matprop database and access library will include the ability to read and write material descriptions that can be exchanged between codes. It will also include an ability to do unit changes, i.e. have the library return parameters in user-specified unit systems. In addition to these, additional material categories can be added (e.g., phase change kinetics, etc.). The Matprop database and access library is part of a larger set of tools used at LLNL for assessing material model behavior. One of these is MSlib, a shared constitutive material model library. Another is the Material Strength Database (MSD), which allows users to compare parameter fits for specific constitutive models to available experimental data. Together with Matprop, these tools create a suite of capabilities that provide state-of-the-art models and parameters for those models to integrated simulation codes. This document is broken into several appendices. Appendix A contains a code example to retrieve several material coefficients. Appendix B contains the API for the Matprop data access library. Appendix C contains a list of the material names and model types currently available in the Matprop database. Appendix D contains a list of the parameter names for the currently recognized model types. Appendix E contains a full xml description of the material Tantalum.« less

Numerical simulation of sloshing with large deforming free surface by MPS-LES method

NASA Astrophysics Data System (ADS)

Pan, Xu-jie; Zhang, Huai-xin; Sun, Xue-yao

2012-12-01

Moving particle semi-implicit (MPS) method is a fully Lagrangian particle method which can easily solve problems with violent free surface. Although it has demonstrated its advantage in ocean engineering applications, it still has some defects to be improved. In this paper, MPS method is extended to the large eddy simulation (LES) by coupling with a sub-particle-scale (SPS) turbulence model. The SPS turbulence model turns into the Reynolds stress terms in the filtered momentum equation, and the Smagorinsky model is introduced to describe the Reynolds stress terms. Although MPS method has the advantage in the simulation of the free surface flow, a lot of non-free surface particles are treated as free surface particles in the original MPS model. In this paper, we use a new free surface tracing method and the key point is "neighbor particle". In this new method, the zone around each particle is divided into eight parts, and the particle will be treated as a free surface particle as long as there are no "neighbor particles" in any two parts of the zone. As the number density parameter judging method has a high efficiency for the free surface particles tracing, we combine it with the neighbor detected method. First, we select out the particles which may be mistreated with high probabilities by using the number density parameter judging method. And then we deal with these particles with the neighbor detected method. By doing this, the new mixed free surface tracing method can reduce the mistreatment problem efficiently. The serious pressure fluctuation is an obvious defect in MPS method, and therefore an area-time average technique is used in this paper to remove the pressure fluctuation with a quite good result. With these improvements, the modified MPS-LES method is applied to simulate liquid sloshing problems with large deforming free surface. Results show that the modified MPS-LES method can simulate the large deforming free surface easily. It can not only capture the large impact pressure accurately on rolling tank wall but also can generate all physical phenomena successfully. The good agreement between numerical and experimental results proves that the modified MPS-LES method is a good CFD methodology in free surface flow simulations.

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field

PubMed Central

Shore, Joel D.; Thurston, George M.

2018-01-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (pH-pK,W) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of pH-pK and W, and 1/W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of 74 lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (pH-pK,W) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions. PMID:26764648

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field.

PubMed

Shore, Joel D; Thurston, George M

2015-12-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (pH-pK,W) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of pH-pK and W, and 1/W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of √74 lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (pH-pK,W) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions.

Charge-regulation phase transition on surface lattices of titratable sites adjacent to electrolyte solutions: An analog of the Ising antiferromagnet in a magnetic field

NASA Astrophysics Data System (ADS)

Shore, Joel D.; Thurston, George M.

2015-12-01

We report a charge-patterning phase transition on two-dimensional square lattices of titratable sites, here regarded as protonation sites, placed in a low-dielectric medium just below the planar interface between this medium and a salt solution. We calculate the work-of-charging matrix of the lattice with use of a linear Debye-Hückel model, as input to a grand-canonical partition function for the distribution of occupancy patterns. For a large range of parameter values, this model exhibits an approximate inverse cubic power-law decrease of the voltage produced by an individual charge, as a function of its in-lattice separation from neighboring titratable sites. Thus, the charge coupling voltage biases the local probabilities of proton binding as a function of the occupancy of sites for many neighbors beyond the nearest ones. We find that even in the presence of these longer-range interactions, the site couplings give rise to a phase transition in which the site occupancies exhibit an alternating, checkerboard pattern that is an analog of antiferromagnetic ordering. The overall strength W of this canonical charge coupling voltage, per unit charge, is a function of the Debye length, the charge depth, the Bjerrum length, and the dielectric coefficients of the medium and the solvent. The alternating occupancy transition occurs above a curve of thermodynamic critical points in the (p H-p K ,W ) plane, the curve representing a charge-regulation analog of variation of the Néel temperature of an Ising antiferromagnet as a function of an applied, uniform magnetic field. The analog of a uniform magnetic field in the antiferromagnet problem is a combination of p H-p K and W , and 1 /W is the analog of the temperature in the antiferromagnet problem. We use Monte Carlo simulations to study the occupancy patterns of the titratable sites, including interactions out to the 37th nearest-neighbor category (a distance of √{74 } lattice constants), first validating simulations through comparison with exact and approximate results for the nearest-neighbor case. We then use the simulations to map the charge-patterning phase boundary in the (p H-p K ,W ) plane. The physical parameters that determine W provide a framework for identifying and designing real surfaces that could exhibit charge-patterning phase transitions.

Catalogue of HI PArameters (CHIPA)

NASA Astrophysics Data System (ADS)

Saponara, J.; Benaglia, P.; Koribalski, B.; Andruchow, I.

2015-08-01

The catalogue of HI parameters of galaxies HI (CHIPA) is the natural continuation of the compilation by M.C. Martin in 1998. CHIPA provides the most important parameters of nearby galaxies derived from observations of the neutral Hydrogen line. The catalogue contains information of 1400 galaxies across the sky and different morphological types. Parameters like the optical diameter of the galaxy, the blue magnitude, the distance, morphological type, HI extension are listed among others. Maps of the HI distribution, velocity and velocity dispersion can also be display for some cases. The main objective of this catalogue is to facilitate the bibliographic queries, through searching in a database accessible from the internet that will be available in 2015 (the website is under construction). The database was built using the open source `` mysql (SQL, Structured Query Language, management system relational database) '', while the website was built with ''HTML (Hypertext Markup Language)'' and ''PHP (Hypertext Preprocessor)''.

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

PubMed

Piehowski, Paul D; Petyuk, Vladislav A; Sandoval, John D; Burnum, Kristin E; Kiebel, Gary R; Monroe, Matthew E; Anderson, Gordon A; Camp, David G; Smith, Richard D

2013-03-01

For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advancement of a soil parameters geodatabase for the modeling assessment of conservation practice outcomes in the United States

USDA-ARS?s Scientific Manuscript database

US-ModSoilParms-TEMPLE is a database composed of a set of geographic databases functionally storing soil-spatial units and soil hydraulic, physical, and chemical parameters for three agriculture management simulation models, SWAT, APEX, and ALMANAC. This paper introduces the updated US-ModSoilParms-...

Intelligent printing system with AMPAC: boot program for printing machine with AMPAC

NASA Astrophysics Data System (ADS)

Yuasa, Tomonori; Mishina, Hiromichi

2000-12-01

The database AMPAC proposes the simple and unified format to describe single parameter of whole field of design, production and management. The database described by the format can be used commonly in any field connected by the network production system, since the description accepts any parameter in any fields and is field independent definition.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Intra-specific competition (crowding) of giant sequoias (Sequoiadendron giganteum)

USGS Publications Warehouse

Stohlgren, Thomas J.

1993-01-01

Information on the size and location of 1916 giant sequoias (Sequoiadendron giganteum (Lindl.) Buchholz) in Muir Grove, Sequoia National Park, in the southern Sierra Nevada of California was used to assess intra-specific crowding. Study objectives were to: (1) determine which parameters associated with intra-specific competition (i.e. size and distance to nearest neighbor, crowding/root system area overlap, or number of neighbors) might be important in spatial pattern development, growth, and survivorship of established giant sequoias; (2) quantify the level of intra-specific crowding of different sized live sequoias based on a model of estimated overlapping root system areas (i.e. an index of relative crowding); (3) compare the level of intra-specific crowding of similarly sized live and dead giant sequoias (less than 30 cm diameter at breast height (dbh) at the time of inventory (1969). Mean distances to the nearest live giant sequoia neighbor were not significantly different (at α = 0.05) for live and dead sequoias in similar size classes. A zone of influence competition model (i.e. index of crowding) based on horizontal overlap of estimated root system areas was developed for 1753 live sequoias. The model, based only on the spatial arrangement of live sequoias, was then tested on dead sequoias of less than 30 cm dbh (n = 163 trees; also recorded in 1969). The dead sequoias had a significantly higher crowding index than 561 live trees of similar diameter. Results showed that dead sequoias of less than 16.6 cm dbh had a significantly greater mean number of live neighbors and mean crowding index than live sequoias of similar size. Intra-specific crowding may be an important mechanism in determining the spatial distribution of sequoias in old-growth forests.

Constructing a logical, regular axis topology from an irregular topology

DOEpatents

Faraj, Daniel A.

2014-07-22

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

Constructing a logical, regular axis topology from an irregular topology

DOEpatents

Faraj, Daniel A.

2014-07-01

Constructing a logical regular topology from an irregular topology including, for each axial dimension and recursively, for each compute node in a subcommunicator until returning to a first node: adding to a logical line of the axial dimension a neighbor specified in a nearest neighbor list; calling the added compute node; determining, by the called node, whether any neighbor in the node's nearest neighbor list is available to add to the logical line; if a neighbor in the called compute node's nearest neighbor list is available to add to the logical line, adding, by the called compute node to the logical line, any neighbor in the called compute node's nearest neighbor list for the axial dimension not already added to the logical line; and, if no neighbor in the called compute node's nearest neighbor list is available to add to the logical line, returning to the calling compute node.

A quasi-dense matching approach and its calibration application with Internet photos.

PubMed

Wan, Yanli; Miao, Zhenjiang; Wu, Q M Jonathan; Wang, Xifu; Tang, Zhen; Wang, Zhifei

2015-03-01

This paper proposes a quasi-dense matching approach to the automatic acquisition of camera parameters, which is required for recovering 3-D information from 2-D images. An affine transformation-based optimization model and a new matching cost function are used to acquire quasi-dense correspondences with high accuracy in each pair of views. These correspondences can be effectively detected and tracked at the sub-pixel level in multiviews with our neighboring view selection strategy. A two-layer iteration algorithm is proposed to optimize 3-D quasi-dense points and camera parameters. In the inner layer, different optimization strategies based on local photometric consistency and a global objective function are employed to optimize the 3-D quasi-dense points and camera parameters, respectively. In the outer layer, quasi-dense correspondences are resampled to guide a new estimation and optimization process of the camera parameters. We demonstrate the effectiveness of our algorithm with several experiments.

Genotypic diversity of Mycobacterium tuberculosis in Buenos Aires, Argentina.

PubMed

Monteserin, Johana; Paul, Roxana; Gravina, Elida; Reniero, Ana; Hernandez, Teresa; Mazzeo, Eduardo; Togneri, Ana; Simboli, Norberto; López, Beatriz; Couvin, David; Rastogi, Nalin; Ritacco, Viviana

2018-04-06

Buenos Aires is an overpopulated port city historically inhabited by people of European descent. Together with its broader metropolitan area, the city exhibits medium tuberculosis rates, and receives migrants, mainly from tuberculosis highly endemic areas of Argentina and neighboring countries. This work was aimed to gain insight into the Mycobacterium tuberculosis population structure in two suburban districts of Buenos Aires which are illustrative of the overall situation of tuberculosis in Argentina. The Lineage 4 Euro-American accounted for >99% of the 816 isolates analyzed (one per patient). Frequencies of spoligotype families were T 35.9%, LAM 33.2%, Haarlem 19.5%, S 3.2%, X 1.5%, Ural 0.7%, BOV 0.2%, Beijing 0.2%, and Cameroon 0.2%. Unknown signatures accounted for 5.3% isolates. Of 55 spoligotypes not matching any extant shared international type (SIT) in SITVIT database, 22 fitted into 15 newly-issued SITs. Certain autochthonous South American genotypes were found to be actively evolving. LAM3, which is wild type for RD rio , was the predominant LAM subfamily in both districts and the RD rio signature was rare among autochthonous, newly created, SITs and orphan patterns. Two genotypes that are rarely observed in neighboring countries ̶ SIT2/H2 and SIT159/T1 Tuscany ̶ were conspicuously represented in Argentina. The infrequent Beijing patterns belonged to Peruvian patients. We conclude that the genotype diversity observed reflects the influence of the Hispanic colonization and more recent immigration waves from Mediterranean and neighboring countries. Unlike in Brazil, the RD rio type does not play a major role in the tuberculosis epidemic in Buenos Aires. Copyright © 2018 Elsevier B.V. All rights reserved.

Examining the social porosity of environmental features on neighborhood sociability and attachment.

PubMed

Hipp, John R; Corcoran, Jonathan; Wickes, Rebecca; Li, Tiebei

2014-01-01

The local neighborhood forms an integral part of our lives. It provides the context through which social networks are nurtured and the foundation from which a sense of attachment and cohesion with fellow residents can be established. Whereas much of the previous research has examined the role of social and demographic characteristic in relation to the level of neighboring and cohesion, this paper explores whether particular environmental features in the neighborhood affect social porosity. We define social porosity as the degree to which social ties flow over the surface of a neighborhood. The focus of our paper is to examine the extent to which a neighborhood's environmental features impede the level of social porosity present among residents. To do this, we integrate data from the census, topographic databases and a 2010 survey of 4,351 residents from 146 neighborhoods in Australia. The study introduces the concepts of wedges and social holes. The presence of two sources of wedges is measured: rivers and highways. The presence of two sources of social holes is measured: parks and industrial areas. Borrowing from the geography literature, several measures are constructed to capture how these features collectively carve up the physical environment of neighborhoods. We then consider how this influences residents' neighboring behavior, their level of attachment to the neighborhood and their sense of neighborhood cohesion. We find that the distance of a neighborhood to one form of social hole-industrial areas-has a particularly strong negative effect on all three dependent variables. The presence of the other form of social hole-parks-has a weaker negative effect. Neighborhood wedges also impact social interaction. Both the length of a river and the number of highway fragments in a neighborhood has a consistent negative effect on neighboring, attachment and cohesion.

PURY: a database of geometric restraints of hetero compounds for refinement in complexes with macromolecular structures.

PubMed

Andrejasic, Miha; Praaenikar, Jure; Turk, Dusan

2008-11-01

The number and variety of macromolecular structures in complex with ;hetero' ligands is growing. The need for rapid delivery of correct geometric parameters for their refinement, which is often crucial for understanding the biological relevance of the structure, is growing correspondingly. The current standard for describing protein structures is the Engh-Huber parameter set. It is an expert data set resulting from selection and analysis of the crystal structures gathered in the Cambridge Structural Database (CSD). Clearly, such a manual approach cannot be applied to the vast and ever-growing number of chemical compounds. Therefore, a database, named PURY, of geometric parameters of chemical compounds has been developed, together with a server that accesses it. PURY is a compilation of the whole CSD. It contains lists of atom classes and bonds connecting them, as well as angle, chirality, planarity and conformation parameters. The current compilation is based on CSD 5.28 and contains 1978 atom classes and 32,702 bonding, 237,068 angle, 201,860 dihedral and 64,193 improper geometric restraints. Analysis has confirmed that the restraints from the PURY database are suitable for use in macromolecular crystal structure refinement and should be of value to the crystallographic community. The database can be accessed through the web server http://pury.ijs.si/, which creates topology and parameter files from deposited coordinates in suitable forms for the refinement programs MAIN, CNS and REFMAC. In the near future, the server will move to the CSD website http://pury.ccdc.cam.ac.uk/.

Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

PubMed Central

2013-01-01

Background The learning active subnetworks problem involves finding subnetworks of a bio-molecular network that are active in a particular condition. Many approaches integrate observation data (e.g., gene expression) with the network topology to find candidate subnetworks. Increasingly, pathway databases contain additional annotation information that can be mined to improve prediction accuracy, e.g., interaction mechanism (e.g., transcription, microRNA, cleavage) annotations. We introduce a mechanism-based approach to active subnetwork recovery which exploits such annotations. We suggest that neighboring interactions in a network tend to be co-activated in a way that depends on the “correlation” of their mechanism annotations. e.g., neighboring phosphorylation and de-phosphorylation interactions may be more likely to be co-activated than neighboring phosphorylation and covalent bonding interactions. Results Our method iteratively learns the mechanism correlations and finds the most likely active subnetwork. We use a probabilistic graphical model with a Markov Random Field component which creates dependencies between the states (active or non-active) of neighboring interactions, that incorporates a mechanism-based component to the function. We apply a heuristic-based EM-based algorithm suitable for the problem. We validated our method’s performance using simulated data in networks downloaded from GeneGO against the same approach without the mechanism-based component, and two other existing methods. We validated our methods performance in correctly recovering (1) the true interaction states, and (2) global network properties of the original network against these other methods. We applied our method to networks generated from time-course gene expression studies in angiogenesis and lung organogenesis and validated the findings from a biological perspective against current literature. Conclusions The advantage of our mechanism-based approach is best seen in networks composed of connected regions with a large number of interactions annotated with a subset of mechanisms, e.g., a regulatory region of transcription interactions, or a cleavage cascade region. When applied to real datasets, our method recovered novel and biologically meaningful putative interactions, e.g., interactions from an integrin signaling pathway using the angiogenesis dataset, and a group of regulatory microRNA interactions in an organogenesis network. PMID:23432934

Kinetic parameters of cholinesterase interactions with organophosphates: retrieval and comparison tools available through ESTHER database: ESTerases, alpha/beta Hydrolase Enzymes and Relatives.

PubMed

Chatonnet, A; Hotelier, T; Cousin, X

1999-05-14

Cholinesterases are targets for organophosphorus compounds which are used as insecticides, chemical warfare agents and drugs for the treatment of disease such as glaucoma, or parasitic infections. The widespread use of these chemicals explains the growing of this area of research and the ever increasing number of sequences, structures, or biochemical data available. Future advances will depend upon effective management of existing information as well as upon creation of new knowledge. The ESTHER database goal is to facilitate retrieval and comparison of data about structure and function of proteins presenting the alpha/beta hydrolase fold. Protein engineering and in vitro production of enzymes allow direct comparison of biochemical parameters. Kinetic parameters of enzymatic reactions are now included in the database. These parameters can be searched and compared with a table construction tool. ESTHER can be reached through internet (http://www.ensam.inra.fr/cholinesterase). The full database or the specialised X-window Client-server system can be downloaded from our ftp server (ftp://ftp.toulouse.inra.fr./pub/esther). Forms can be used to send updates or corrections directly from the web.

Database Constraints Applied to Metabolic Pathway Reconstruction Tools

PubMed Central

Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

2014-01-01

Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes. PMID:25202745

Tree chemistry database (version 1.0)

Treesearch

Linda H. Pardo; Molly Robin-Abbott; Natasha Duarte; Eric K. Miller

2005-01-01

The Tree Chemistry Database is a relational database of C, N, P, K, Ca, Mg, Mn, and Al concentrations in bole bark, bole wood, branches, twigs, and foliage. Compiled from data in 218 articles and publications, the database contains reported nutrient and biomass values for tree species in the Northeastern United States. Nutrient data can be sorted on parameters such as...

Are people living next to mobile phone base stations more strained? Relationship of health concerns, self-estimated distance to base station, and psychological parameters.

PubMed

Augner, Christoph; Hacker, Gerhard W

2009-12-01

Coeval with the expansion of mobile phone technology and the associated obvious presence of mobile phone base stations, some people living close to these masts reported symptoms they attributed to electromagnetic fields (EMF). Public and scientific discussions arose with regard to whether these symptoms were due to EMF or were nocebo effects. The aim of this study was to find out if people who believe that they live close to base stations show psychological or psychobiological differences that would indicate more strain or stress. Furthermore, we wanted to detect the relevant connections linking self-estimated distance between home and the next mobile phone base station (DBS), daily use of mobile phone (MPU), EMF-health concerns, electromagnetic hypersensitivity, and psychological strain parameters. Fifty-seven participants completed standardized and non-standardized questionnaires that focused on the relevant parameters. In addition, saliva samples were used as an indication to determine the psychobiological strain by concentration of alpha-amylase, cortisol, immunoglobulin A (IgA), and substance P. Self-declared base station neighbors (DBS

The effects of dynamical synapses on firing rate activity: a spiking neural network model.

PubMed

Khalil, Radwa; Moftah, Marie Z; Moustafa, Ahmed A

2017-11-01

Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

PubMed Central

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2013-01-01

Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. PMID:21917512

Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

PubMed

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2011-11-01

Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (p<0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician's diagnostic impression and the gold standard k=0. 64 (p<0.0001). There was moderate agreement between the physician's diagnostic impression and CDSS k=0.46 (p=0.0008). The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The DREO Elint Browser Utility (DEBU) reference manual

NASA Astrophysics Data System (ADS)

Ford, Barbara; Jones, David

1992-04-01

An electronic intelligent database browsing tool called DEBU has been developed that allows databases such as ELP, Kilting, EWIR, and AFEWC to be reviewed and analyzed from a user-friendly environment on a personal computer. DEBU's basic function is to allow users to examine the contents of user-selected subfiles of user-selected emitters of user-selected databases. DEBU augments this functionality with support for selecting (filtering) and combining subsets of emitters by user-selected attributes such as name, parameter type, or parameter value. DEBU provides facilities for examining histograms and x-y plots of selected parameters, for doing ambiguity analysis and mode level analysis, and for generating and printing a variety of reports. A manual is provided for users of DEBU, including descriptions and illustrations of menus and windows.

IAU MDC Photographic Meteor Orbits Database: Version 2013

NASA Astrophysics Data System (ADS)

Neslušan, L.; Porubčan, V.; Svoreň, J.

2014-05-01

A new 2013 version of the IAU MDC photographic meteor orbits database which is an upgrade of the current 2003 version (Lindblad et al. 2003, EMP 93:249-260) is presented. To the 2003 version additional 292 orbits are added, thus the new version of the database consists of 4,873 meteors with their geophysical and orbital parameters compiled in 41 catalogues. For storing the data, a new format enabling a more simple treatment with the parameters, including the errors of their determination is applied. The data can be downloaded from the IAU MDC web site: http://www.astro.sk/IAUMDC/Ph2013/

Neighboring and Urbanism: Commonality versus Friendship.

ERIC Educational Resources Information Center

Silverman, Carol J.

1986-01-01

Examines a dimension of neighboring that need not assume friendship as the role model. When the model assumes only a sense of connectedness as defining neighboring, then the residential correlation, shown in many studies between urbanism and neighboring, disappears. Theories of neighboring, study variables, methods, and analysis are discussed.…

G4RNA: an RNA G-quadruplex database

PubMed Central

Garant, Jean-Michel; Luce, Mikael J.; Scott, Michelle S.

2015-01-01

Abstract G-quadruplexes (G4) are tetrahelical structures formed from planar arrangement of guanines in nucleic acids. A simple, regular motif was originally proposed to describe G4-forming sequences. More recently, however, formation of G4 was discovered to depend, at least in part, on the contextual backdrop of neighboring sequences. Prediction of G4 folding is thus becoming more challenging as G4 outlier structures, not described by the originally proposed motif, are increasingly reported. Recent observations thus call for a comprehensive tool, capable of consolidating the expanding information on tested G4s, in order to conduct systematic comparative analyses of G4-promoting sequences. The G4RNA Database we propose was designed to help meet the need for easily-retrievable data on known RNA G4s. A user-friendly, flexible query system allows for data retrieval on experimentally tested sequences, from many separate genes, to assess G4-folding potential. Query output sorts data according to sequence position, G4 likelihood, experimental outcomes and associated bibliographical references. G4RNA also provides an ideal foundation to collect and store additional sequence and experimental data, considering the growing interest G4s currently generate. Database URL: scottgroup.med.usherbrooke.ca/G4RNA PMID:26200754

Toward More Accurate Iris Recognition Using Cross-Spectral Matching.

PubMed

Nalla, Pattabhi Ramaiah; Kumar, Ajay

2017-01-01

Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs, which continue to acquire millions of iris images to establish identity among billions. However, with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields model to significantly improve cross-domain iris recognition. The proposed domain adaptation framework based on the naive Bayes nearest neighbor classification uses a real-valued feature representation, which is capable of learning domain knowledge. Our approach to estimate corresponding visible iris patterns from the synthesis of iris patches in the near infrared iris images achieves outperforming results for the cross-spectral iris recognition. In this paper, a new class of bi-spectral iris recognition system that can simultaneously acquire visible and near infra-red images with pixel-to-pixel correspondences is proposed and evaluated. This paper presents experimental results from three publicly available databases; PolyU cross-spectral iris image database, IIITD CLI and UND database, and achieve outperforming results for the cross-sensor and cross-spectral iris matching.

Testing spatial theories of plant coexistence: no consistent differences in intra- and interspecific interaction distances.

PubMed

Vogt, Deborah R; Murrell, David J; Stoll, Peter

2010-01-01

Plants stand still and interact with their immediate neighbors. Theory has shown that the distances over which these interactions occur may have important consequences for population and community dynamics. In particular, if intraspecific competition occurs over longer distances than interspecific competition (heteromyopia), coexistence can be promoted. We examined how intraspecific and interspecific competition scales with neighbor distance in a target-neighbor greenhouse competition experiment. Individuals from co-occurring forbs from calcareous grasslands were grown in isolation and with single conspecific or heterospecific neighbors at distances of 5, 10, or 15 cm (Plantago lanceolata vs. Plantago media and Hieracium pilosella vs. Prunella grandiflora). Neighbor effects were strong and declined with distance. Interaction distances varied greatly within and between species, but we found no evidence for heteromyopia. Instead, neighbor identity effects were mostly explained by relative size differences between target and neighbor. We found a complex interaction between final neighbor size and identity such that neighbor identity may become important only as the neighbor becomes very large compared with the target individual. Our results suggest that species-specific size differences between neighboring individuals determine both the strength of competitive interactions and the distance over which these interactions occur.

An automated algorithm for determining photometric redshifts of quasars

NASA Astrophysics Data System (ADS)

Wang, Dan; Zhang, Yanxia; Zhao, Yongheng

2010-07-01

We employ k-nearest neighbor algorithm (KNN) for photometric redshift measurement of quasars with the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). KNN is an instance learning algorithm where the result of new instance query is predicted based on the closest training samples. The regressor do not use any model to fit and only based on memory. Given a query quasar, we find the known quasars or (training points) closest to the query point, whose redshift value is simply assigned to be the average of the values of its k nearest neighbors. Three kinds of different colors (PSF, Model or Fiber) and spectral redshifts are used as input parameters, separatively. The combination of the three kinds of colors is also taken as input. The experimental results indicate that the best input pattern is PSF + Model + Fiber colors in all experiments. With this pattern, 59.24%, 77.34% and 84.68% of photometric redshifts are obtained within ▵z < 0.1, 0.2 and 0.3, respectively. If only using one kind of colors as input, the model colors achieve the best performance. However, when using two kinds of colors, the best result is achieved by PSF + Fiber colors. In addition, nearest neighbor method (k = 1) shows its superiority compared to KNN (k ≠ 1) for the given sample.

Adaptive non-local means on local principle neighborhood for noise/artifacts reduction in low-dose CT images.

PubMed

Zhang, Yuanke; Lu, Hongbing; Rong, Junyan; Meng, Jing; Shang, Junliang; Ren, Pinghong; Zhang, Junying

2017-09-01

Low-dose CT (LDCT) technique can reduce the x-ray radiation exposure to patients at the cost of degraded images with severe noise and artifacts. Non-local means (NLM) filtering has shown its potential in improving LDCT image quality. However, currently most NLM-based approaches employ a weighted average operation directly on all neighbor pixels with a fixed filtering parameter throughout the NLM filtering process, ignoring the non-stationary noise nature of LDCT images. In this paper, an adaptive NLM filtering scheme on local principle neighborhoods (PC-NLM) is proposed for structure-preserving noise/artifacts reduction in LDCT images. Instead of using neighboring patches directly, in the PC-NLM scheme, the principle component analysis (PCA) is first applied on local neighboring patches of the target patch to decompose the local patches into uncorrelated principle components (PCs), then a NLM filtering is used to regularize each PC of the target patch and finally the regularized components is transformed to get the target patch in image domain. Especially, in the NLM scheme, the filtering parameter is estimated adaptively from local noise level of the neighborhood as well as the signal-to-noise ratio (SNR) of the corresponding PC, which guarantees a "weaker" NLM filtering on PCs with higher SNR and a "stronger" filtering on PCs with lower SNR. The PC-NLM procedure is iteratively performed several times for better removal of the noise and artifacts, and an adaptive iteration strategy is developed to reduce the computational load by determining whether a patch should be processed or not in next round of the PC-NLM filtering. The effectiveness of the presented PC-NLM algorithm is validated by experimental phantom studies and clinical studies. The results show that it can achieve promising gain over some state-of-the-art methods in terms of artifact suppression and structure preservation. With the use of PCA on local neighborhoods to extract principal structural components, as well as adaptive NLM filtering on PCs of the target patch using filtering parameter estimated based on the local noise level and corresponding SNR, the proposed PC-NLM method shows its efficacy in preserving fine anatomical structures and suppressing noise/artifacts in LDCT images. © 2017 American Association of Physicists in Medicine.

Selective incivility: immigrant groups experience subtle workplace discrimination at different rates.

PubMed

Krings, Franciska; Johnston, Claire; Binggeli, Steve; Maggiori, Christian

2014-10-01

Immigrants play an increasingly important role in local labor markets. Not only do they grow steadily in number but also in cultural, educational, and skill diversity, underlining the necessity to distinguish between immigrant groups when studying discrimination against immigrants. We examined immigrant employees' subtle discrimination experiences in a representative sample in Switzerland, controlling for dispositional influences. Results showed that mainly members of highly competitive immigrant groups, from immediate neighbor countries, experienced workplace incivility and that these incivility experiences were related to higher likelihoods of perceived discrimination at work. This research confirms recent accounts that successful but disliked groups are particularly likely to experience subtle interpersonal discrimination. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Disruption Warning Database Development and Exploratory Machine Learning Studies on Alcator C-Mod

NASA Astrophysics Data System (ADS)

Montes, Kevin; Rea, Cristina; Granetz, Robert

2017-10-01

A database of about 1800 shots from the 2015 campaign on the Alcator C-Mod tokamak is assembled, including disruptive and non-disruptive discharges. The database consists of 40 relevant plasma parameters with data taken from 160k time slices. In order to investigate the possibility of developing a robust disruption prediction algorithm that is tokamak-independent, we focused machine learning studies on a subset of dimensionless parameters such as βp, n /nG , etc. The Random Forests machine learning algorithm provides insight on the available data set by ranking the relative importance of the input features. Its application on the C-Mod database, however, reveals that virtually no one parameter has more importance than any other, and that its classification algorithm has a low rate of successfully predicted samples, as well as poor false positive and false negative rates. Comparing the analysis of this algorithm on the C-Mod database with its application to a similar database on DIII-D, we conclude that disruption prediction may not be feasible on C-Mod. This conclusion is supported by empirical observations that most C-Mod disruptions are caused by radiative collapse due to molybdenum from the first wall, which happens on just a 1-2ms timescale. Supported by the US Dept. of Energy under DE-FC02-99ER54512 and DE-FC02-04ER54698.

Phase diagram and criticality of the two-dimensional prisoner's dilemma model

NASA Astrophysics Data System (ADS)

Santos, M.; Ferreira, A. L.; Figueiredo, W.

2017-07-01

The stationary states of the prisoner's dilemma model are studied on a square lattice taking into account the role of a noise parameter in the decision-making process. Only first neighboring players—defectors and cooperators—are considered in each step of the game. Through Monte Carlo simulations we determined the phase diagrams of the model in the plane noise versus the temptation to defect for a large range of values of the noise parameter. We observed three phases: cooperators and defectors absorbing phases, and a coexistence phase between them. The phase transitions as well as the critical exponents associated with them were determined using both static and dynamical scaling laws.

Hubert: Software for efficient analysis of in-situ nuclear forward scattering experiments

NASA Astrophysics Data System (ADS)

Vrba, Vlastimil; Procházka, Vít; Smrčka, David; Miglierini, Marcel

2016-10-01

Combination of short data acquisition time and local investigation of a solid state through hyperfine parameters makes nuclear forward scattering (NFS) a unique experimental technique for investigation of fast processes. However, the total number of acquired NFS time spectra may be very high. Therefore an efficient way of the data evaluation is needed. In this paper we report the development of Hubert software package as a response to the rapidly developing field of in-situ NFS experiments. Hubert offers several useful features for data files processing and could significantly shorten the evaluation time by using a simple connection between the neighboring time spectra through their input and output parameter values.

Resilient Distributed Estimation Through Adversary Detection

NASA Astrophysics Data System (ADS)

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2018-05-01

This paper studies resilient multi-agent distributed estimation of an unknown vector parameter when a subset of the agents is adversarial. We present and analyze a Flag Raising Distributed Estimator ($\\mathcal{FRDE}$) that allows the agents under attack to perform accurate parameter estimation and detect the adversarial agents. The $\\mathcal{FRDE}$ algorithm is a consensus+innovations estimator in which agents combine estimates of neighboring agents (consensus) with local sensing information (innovations). We establish that, under $\\mathcal{FRDE}$, either the uncompromised agents' estimates are almost surely consistent or the uncompromised agents detect compromised agents if and only if the network of uncompromised agents is connected and globally observable. Numerical examples illustrate the performance of $\\mathcal{FRDE}$.

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

Assessing the quality of life history information in publicly available databases.

PubMed

Thorson, James T; Cope, Jason M; Patrick, Wesley S

2014-01-01

Single-species life history parameters are central to ecological research and management, including the fields of macro-ecology, fisheries science, and ecosystem modeling. However, there has been little independent evaluation of the precision and accuracy of the life history values in global and publicly available databases. We therefore develop a novel method based on a Bayesian errors-in-variables model that compares database entries with estimates from local experts, and we illustrate this process by assessing the accuracy and precision of entries in FishBase, one of the largest and oldest life history databases. This model distinguishes biases among seven life history parameters, two types of information available in FishBase (i.e., published values and those estimated from other parameters), and two taxa (i.e., bony and cartilaginous fishes) relative to values from regional experts in the United States, while accounting for additional variance caused by sex- and region-specific life history traits. For published values in FishBase, the model identifies a small positive bias in natural mortality and negative bias in maximum age, perhaps caused by unacknowledged mortality caused by fishing. For life history values calculated by FishBase, the model identified large and inconsistent biases. The model also demonstrates greatest precision for body size parameters, decreased precision for values derived from geographically distant populations, and greatest between-sex differences in age at maturity. We recommend that our bias and precision estimates be used in future errors-in-variables models as a prior on measurement errors. This approach is broadly applicable to global databases of life history traits and, if used, will encourage further development and improvements in these databases.

Phase behavior of charged colloids at a fluid interface

NASA Astrophysics Data System (ADS)

Kelleher, Colm P.; Guerra, Rodrigo E.; Hollingsworth, Andrew D.; Chaikin, Paul M.

2017-02-01

We study the phase behavior of a system of charged colloidal particles that are electrostatically bound to an almost flat interface between two fluids. We show that, despite the fact that our experimental system consists of only 103-104 particles, the phase behavior is consistent with the theory of melting due to Kosterlitz, Thouless, Halperin, Nelson, and Young. Using spatial and temporal correlations of the bond-orientational order parameter, we classify our samples into solid, isotropic fluid, and hexatic phases. We demonstrate that the topological defect structure we observe in each phase corresponds to the predictions of Kosterlitz-Thouless-Halperin-Nelson-Young theory. By measuring the dynamic Lindemann parameter γL(τ ) and the non-Gaussian parameter α2(τ ) of the displacements of the particles relative to their neighbors, we show that each of the phases displays distinctive dynamical behavior.

Automatic tissue characterization from ultrasound imagery

NASA Astrophysics Data System (ADS)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

Direction of Coupling from Phases of Interacting Oscillators: A Permutation Information Approach

NASA Astrophysics Data System (ADS)

Bahraminasab, A.; Ghasemi, F.; Stefanovska, A.; McClintock, P. V. E.; Kantz, H.

2008-02-01

We introduce a directionality index for a time series based on a comparison of neighboring values. It can distinguish unidirectional from bidirectional coupling, as well as reveal and quantify asymmetry in bidirectional coupling. It is tested on a numerical model of coupled van der Pol oscillators, and applied to cardiorespiratory data from healthy subjects. There is no need for preprocessing and fine-tuning the parameters, which makes the method very simple, computationally fast and robust.

Coevolutionary network approach to cultural dynamics controlled by intolerance

NASA Astrophysics Data System (ADS)

Gracia-Lázaro, Carlos; Quijandría, Fernando; Hernández, Laura; Floría, Luis Mario; Moreno, Yamir

2011-12-01

Starting from Axelrod's model of cultural dissemination, we introduce a rewiring probability, enabling agents to cut the links with their unfriendly neighbors if their cultural similarity is below a tolerance parameter. For low values of tolerance, rewiring promotes the convergence to a frozen monocultural state. However, intermediate tolerance values prevent rewiring once the network is fragmented, resulting in a multicultural society even for values of initial cultural diversity in which the original Axelrod model reaches globalization.

Fluctuating asymmetry and testing isolation of Montana grizzly bear populations

USGS Publications Warehouse

Picton, Harold D.; Palmisciano, Daniel A.; Nelson, Gerald

1990-01-01

Fluctuating asymmetry of adult skulls was used to test he genetic isolation of the Yellowstone grizzly bear population from its nearest neighbor. An overall summary statistic was used in addition to 16 other parameters. Tests found the males of the Yellowstone populaion to be more vaiable than those of the North Conitinental Divide Exosystem. Evidence for precipitaiton effects is also included. This test tends to support the existing management haypothesis that the Yellowstone population is isolatied.

Finite-Horizon $H_\\infty $ Consensus for Multiagent Systems With Redundant Channels via An Observer-Type Event-Triggered Scheme.

PubMed

Xu, Wenying; Wang, Zidong; Ho, Daniel W C

2018-05-01

This paper is concerned with the finite-horizon consensus problem for a class of discrete time-varying multiagent systems with external disturbances and missing measurements. To improve the communication reliability, redundant channels are introduced and the corresponding protocol is constructed for the information transmission over redundant channels. An event-triggered scheme is adopted to determine whether the information of agents should be transmitted to their neighbors. Subsequently, an observer-type event-triggered control protocol is proposed based on the latest received neighbors' information. The purpose of the addressed problem is to design a time-varying controller based on the observed information to achieve the consensus performance in a finite horizon. By utilizing a constrained recursive Riccati difference equation approach, some sufficient conditions are obtained to guarantee the consensus performance, and the controller parameters are also designed. Finally, a numerical example is provided to demonstrate the desired reliability of redundant channels and the effectiveness of the event-triggered control protocol.

Vibrational and elastic properties of silicate spinels A2SiO4 (A = Mg, Fe, Ni, and Co)

NASA Astrophysics Data System (ADS)

Kushwaha, A. K.; Ma, C.-G.; Brik, M. G.; Akbudak, S.

2018-06-01

A six-parameter bond-bending force constant model is used to calculate the zone-center (Γ = 0) Raman and infrared phonon mode frequencies, elastic constants and related properties, the Debye temperatures, and sound velocities along high-symmetry directions for A2SiO4 (A = Mg, Fe, Ni, and Co) spinels. The main outcomes of the calculations are that the interactions between Si and O atoms (first-neighbor interaction) are stronger than those between A and Oatoms (A = Mg, Fe, Ni, and Co) (second-neighbor interaction). The elastic constants C11, C12, and C44 decrease in the order Mg > Fe > Ni > Co. The calculated bulk modulus, Poisson's ratio, and anisotropy decrease in the sequence Fe2SiO4 → Ni2SiO4 → Co2SiO4 → Mg2SiO4. On comparison, we find overall good agreement with the available experimental and previously calculated data.

Floating phase in the one-dimensional transverse axial next-nearest-neighbor Ising model.

PubMed

Chandra, Anjan Kumar; Dasgupta, Subinay

2007-02-01

To study the ground state of an axial next-nearest-neighbor Ising chain under transverse field as a function of frustration parameter kappa and field strength Gamma, we present here two different perturbative analyses. In one, we consider the (known) ground state at kappa=0.5 and Gamma=0 as the unperturbed state and treat an increase of the field from 0 to Gamma coupled with an increase of kappa from 0.5 to 0.5+rGamma/J as perturbation. The first-order perturbation correction to eigenvalue can be calculated exactly and we could conclude that there are only two phase-transition lines emanating from the point kappa=0.5, Gamma=0. In the second perturbation scheme, we consider the number of domains of length 1 as the perturbation and obtain the zeroth-order eigenfunction for the perturbed ground state. From the longitudinal spin-spin correlation, we conclude that floating phase exists for small values of transverse field over the entire region intermediate between the ferromagnetic phase and antiphase.

Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

PubMed

Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

2015-09-01

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions

NASA Technical Reports Server (NTRS)

Rice, John Jeremy; Stolovitzky, Gustavo; Tu, Yuhai; de Tombe, Pieter P.; Bers, D. M. (Principal Investigator)

2003-01-01

We have developed a model of cardiac thin filament activation using an Ising model approach from equilibrium statistical physics. This model explicitly represents nearest-neighbor interactions between 26 troponin/tropomyosin units along a one-dimensional array that represents the cardiac thin filament. With transition rates chosen to match experimental data, the results show that the resulting force-pCa (F-pCa) relations are similar to Hill functions with asymmetries, as seen in experimental data. Specifically, Hill plots showing (log(F/(1-F)) vs. log [Ca]) reveal a steeper slope below the half activation point (Ca(50)) compared with above. Parameter variation studies show interplay of parameters that affect the apparent cooperativity and asymmetry in the F-pCa relations. The model also predicts that Ca binding is uncooperative for low [Ca], becomes steeper near Ca(50), and becomes uncooperative again at higher [Ca]. The steepness near Ca(50) mirrors the steep F-pCa as a result of thermodynamic considerations. The model also predicts that the correlation between troponin/tropomyosin units along the one-dimensional array quickly decays at high and low [Ca], but near Ca(50), high correlation occurs across the whole array. This work provides a simple model that can account for the steepness and shape of F-pCa relations that other models fail to reproduce.

Hash Bit Selection for Nearest Neighbor Search.

PubMed

Xianglong Liu; Junfeng He; Shih-Fu Chang

2017-11-01

To overcome the barrier of storage and computation when dealing with gigantic-scale data sets, compact hashing has been studied extensively to approximate the nearest neighbor search. Despite the recent advances, critical design issues remain open in how to select the right features, hashing algorithms, and/or parameter settings. In this paper, we address these by posing an optimal hash bit selection problem, in which an optimal subset of hash bits are selected from a pool of candidate bits generated by different features, algorithms, or parameters. Inspired by the optimization criteria used in existing hashing algorithms, we adopt the bit reliability and their complementarity as the selection criteria that can be carefully tailored for hashing performance in different tasks. Then, the bit selection solution is discovered by finding the best tradeoff between search accuracy and time using a modified dynamic programming method. To further reduce the computational complexity, we employ the pairwise relationship among hash bits to approximate the high-order independence property, and formulate it as an efficient quadratic programming method that is theoretically equivalent to the normalized dominant set problem in a vertex- and edge-weighted graph. Extensive large-scale experiments have been conducted under several important application scenarios of hash techniques, where our bit selection framework can achieve superior performance over both the naive selection methods and the state-of-the-art hashing algorithms, with significant accuracy gains ranging from 10% to 50%, relatively.

Finite-Horizon H∞ Consensus Control of Time-Varying Multiagent Systems With Stochastic Communication Protocol.

PubMed

Zou, Lei; Wang, Zidong; Gao, Huijun; Alsaadi, Fuad E

2017-03-31

This paper is concerned with the distributed H∞ consensus control problem for a discrete time-varying multiagent system with the stochastic communication protocol (SCP). A directed graph is used to characterize the communication topology of the multiagent network. The data transmission between each agent and the neighboring ones is implemented via a constrained communication channel where only one neighboring agent is allowed to transmit data at each time instant. The SCP is applied to schedule the signal transmission of the multiagent system. A sequence of random variables is utilized to capture the scheduling behavior of the SCP. By using the mapping technology combined with the Hadamard product, the closed-loop multiagent system is modeled as a time-varying system with a stochastic parameter matrix. The purpose of the addressed problem is to design a cooperative controller for each agent such that, for all probabilistic scheduling behaviors, the H∞ consensus performance is achieved over a given finite horizon for the closed-loop multiagent system. A necessary and sufficient condition is derived to ensure the H∞ consensus performance based on the completing squares approach and the stochastic analysis technique. Then, the controller parameters are obtained by solving two coupled backward recursive Riccati difference equations. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.

Flexible embedding of networks

NASA Astrophysics Data System (ADS)

Fernandez-Gracia, Juan; Buckee, Caroline; Onnela, Jukka-Pekka

We introduce a model for embedding one network into another, focusing on the case where network A is much bigger than network B. Nodes from network A are assigned to the nodes in network B using an algorithm where we control the extent of localization of node placement in network B using a single parameter. Starting from an unassigned node in network A, called the source node, we first map this node to a randomly chosen node in network B, called the target node. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk based approach. To assign each neighbor of the source node to one of the nodes in network B, we perform a random walk starting from the target node with stopping probability α. We repeat this process until all nodes in network A have been mapped to the nodes of network B. The simplicity of the model allows us to calculate key quantities of interest in closed form. By varying the parameter α, we are able to produce embeddings from very local (α = 1) to very global (α --> 0). We show how our calculations fit the simulated results, and we apply the model to study how social networks are embedded in geography and how the neurons of C. Elegans are embedded in the surrounding volume.

The loss of a hydrogen bond: Thermodynamic contributions of a non-standard nucleotide

PubMed Central

Jolley, Elizabeth A.

2017-01-01

Abstract Non-standard nucleotides are ubiquitous in RNA. Thermodynamic studies with RNA duplexes containing non-standard nucleotides, whether incorporated naturally or chemically, can provide insight into the stability of Watson–Crick pairs and the role of specific functional groups in stabilizing a Watson–Crick pair. For example, an A-U, inosine•U and pseudouridine•A pair each form two hydrogen bonds. However, an RNA duplex containing a central I•U pair or central Ψ•A pair is 2.4 kcal/mol less stable or 1.7 kcal/mol more stable, respectively, than the corresponding duplex containing an A-U pair. In the non-standard nucleotide purine, hydrogen replaces the exocyclic amino group of A. This replacement results in a P•U pair containing only one hydrogen bond. Optical melting studies were performed with RNA duplexes containing P•U pairs adjacent to different nearest neighbors. The resulting thermodynamic parameters were compared to RNA duplexes containing A-U pairs in order to determine the contribution of the hydrogen bond involving the exocyclic amino group. Results indicate a loss of 1.78 kcal/mol, on average, when an internal P•U replaces A-U in an RNA duplex. This value is compared to the thermodynamics of a hydrogen bond determined by similar methods. Nearest neighbor parameters were derived for use in free energy and secondary structure prediction software. PMID:28180321

Automatic Seizure Detection Based on Morphological Features Using One-Dimensional Local Binary Pattern on Long-Term EEG.

PubMed

Shanir, P P Muhammed; Khan, Kashif Ahmad; Khan, Yusuf Uzzaman; Farooq, Omar; Adeli, Hojjat

2017-12-01

Epileptic neurological disorder of the brain is widely diagnosed using the electroencephalography (EEG) technique. EEG signals are nonstationary in nature and show abnormal neural activity during the ictal period. Seizures can be identified by analyzing and obtaining features of EEG signal that can detect these abnormal activities. The present work proposes a novel morphological feature extraction technique based on the local binary pattern (LBP) operator. LBP provides a unique decimal value to a sample point by weighing the binary outcomes after thresholding the neighboring samples with the present sample point. These LBP values assist in capturing the rising and falling edges of the EEG signal, thus providing a morphologically featured discriminating pattern for epilepsy detection. In the present work, the variability in the LBP values is measured by calculating the sum of absolute difference of the consecutive LBP values. Interquartile range is calculated over the preprocessed EEG signal to provide dispersion measure in the signal. For classification purpose, K-nearest neighbor classifier is used, and the performance is evaluated on 896.9 hours of data from CHB-MIT continuous EEG database. Mean accuracy of 99.7% and mean specificity of 99.8% is obtained with average false detection rate of 0.47/h and sensitivity of 99.2% for 136 seizures.

The dispersion-focalization theory of sound systems

NASA Astrophysics Data System (ADS)

Schwartz, Jean-Luc; Abry, Christian; Boë, Louis-Jean; Vallée, Nathalie; Ménard, Lucie

2005-04-01

The Dispersion-Focalization Theory states that sound systems in human languages are shaped by two major perceptual constraints: dispersion driving auditory contrast towards maximal or sufficient values [B. Lindblom, J. Phonetics 18, 135-152 (1990)] and focalization driving auditory spectra towards patterns with close neighboring formants. Dispersion is computed from the sum of the inverse squared inter-spectra distances in the (F1, F2, F3, F4) space, using a non-linear process based on the 3.5 Bark critical distance to estimate F2'. Focalization is based on the idea that close neighboring formants produce vowel spectra with marked peaks, easier to process and memorize in the auditory system. Evidence for increased stability of focal vowels in short-term memory was provided in a discrimination experiment on adult French subjects [J. L. Schwartz and P. Escudier, Speech Comm. 8, 235-259 (1989)]. A reanalysis of infant discrimination data shows that focalization could well be the responsible for recurrent discrimination asymmetries [J. L. Schwartz et al., Speech Comm. (in press)]. Recent data about children vowel production indicate that focalization seems to be part of the perceptual templates driving speech development. The Dispersion-Focalization Theory produces valid predictions for both vowel and consonant systems, in relation with available databases of human languages inventories.

Phylogenetic and bioinformatic analysis of gap junction-related proteins, innexins, pannexins and connexins.

PubMed

Fushiki, Daisuke; Hamada, Yasuo; Yoshimura, Ryoichi; Endo, Yasuhisa

2010-04-01

All multi-cellular animals, including hydra, insects and vertebrates, develop gap junctions, which communicate directly with neighboring cells. Gap junctions consist of protein families called connexins in vertebrates and innexins in invertebrates. Connexins and innexins have no homology in their amino acid sequence, but both are thought to have some similar characteristics, such as a tetra-membrane-spanning structure, formation of a channel by hexamer, and transmission of small molecules (e.g. ions) to neighboring cells. Pannexins were recently identified as a homolog of innexins in vertebrate genomes. Although pannexins are thought to share the function of intercellular communication with connexins and innexins, there is little information about the relationship among these three protein families of gap junctions. We phylgenetically and bioinformatically examined these protein families and other tetra-membrane-spanning proteins using a database and three analytical softwares. The clades formed by pannexin families do not belong to the species classification but do to paralogs of each member of pannexins. Amino acid sequences of pannexins are closely related to those of innexins but less to those of connexins. These data suggest that innexins and pannexins have a common origin, but the relationship between innexins/pannexins and connexins is as slight as that of other tetra-membrane-spanning members.

dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins.

PubMed

Huang, Kai-Yao; Su, Min-Gang; Kao, Hui-Ju; Hsieh, Yun-Chung; Jhong, Jhih-Hua; Cheng, Kuang-Hao; Huang, Hsien-Da; Lee, Tzong-Yi

2016-01-04

Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Active learning for solving the incomplete data problem in facial age classification by the furthest nearest-neighbor criterion.

PubMed

Wang, Jian-Gang; Sung, Eric; Yau, Wei-Yun

2011-07-01

Facial age classification is an approach to classify face images into one of several predefined age groups. One of the difficulties in applying learning techniques to the age classification problem is the large amount of labeled training data required. Acquiring such training data is very costly in terms of age progress, privacy, human time, and effort. Although unlabeled face images can be obtained easily, it would be expensive to manually label them on a large scale and getting the ground truth. The frugal selection of the unlabeled data for labeling to quickly reach high classification performance with minimal labeling efforts is a challenging problem. In this paper, we present an active learning approach based on an online incremental bilateral two-dimension linear discriminant analysis (IB2DLDA) which initially learns from a small pool of labeled data and then iteratively selects the most informative samples from the unlabeled set to increasingly improve the classifier. Specifically, we propose a novel data selection criterion called the furthest nearest-neighbor (FNN) that generalizes the margin-based uncertainty to the multiclass case and which is easy to compute, so that the proposed active learning algorithm can handle a large number of classes and large data sizes efficiently. Empirical experiments on FG-NET and Morph databases together with a large unlabeled data set for age categorization problems show that the proposed approach can achieve results comparable or even outperform a conventionally trained active classifier that requires much more labeling effort. Our IB2DLDA-FNN algorithm can achieve similar results much faster than random selection and with fewer samples for age categorization. It also can achieve comparable results with active SVM but is much faster than active SVM in terms of training because kernel methods are not needed. The results on the face recognition database and palmprint/palm vein database showed that our approach can handle problems with large number of classes. Our contributions in this paper are twofold. First, we proposed the IB2DLDA-FNN, the FNN being our novel idea, as a generic on-line or active learning paradigm. Second, we showed that it can be another viable tool for active learning of facial age range classification.

Study of Mycobacterium tuberculosis Complex Genotypic Diversity in Malaysia Reveals a Predominance of Ancestral East-African-Indian Lineage with a Malaysia-Specific Signature

PubMed Central

Ismail, Fazli; Couvin, David; Farakhin, Izzah; Abdul Rahman, Zaidah; Rastogi, Nalin; Suraiya, Siti

2014-01-01

Background Tuberculosis (TB) still constitutes a major public health problem in Malaysia. The identification and genotyping based characterization of Mycobacterium tuberculosis complex (MTBC) isolates causing the disease is important to determine the effectiveness of the control and surveillance programs. Objectives This study intended a first assessment of spoligotyping-based MTBC genotypic diversity in Malaysia followed by a comparison of strains with those prevailing in neighboring countries by comparison with an international MTBC genotyping database. Methods Spoligotyping was performed on a total of 220 M. tuberculosis clinical isolates collected in Kelantan and Kuala Lumpur. The results were compared with the SITVIT2 international database of the Pasteur Institute of Guadeloupe. Results Spoligotyping revealed 77 different patterns: 22 corresponded to orphan patterns while 55 patterns containing 198 isolates were assigned a Spoligo International Type (SIT) designation in the database (the latter included 6 newly created SITs). The eight most common SITs grouped 141 isolates (5 to 56 strains per cluster) as follows: SIT1/Beijing, n = 56, 25.5%; SIT745/EAI1-SOM, n = 33, 15.0%; SIT591/EAI6-BGD1, n = 13, 5.9%; SIT256/EAI5, n = 12, 5.5%; SIT236/EAI5, n = 10, 4.6%; SIT19/EAI2-Manila, n = 9, 4.1%; SIT89/EAI2-Nonthaburi, n = 5, 2.3%; and SIT50/H3, n = 3, 1.4%. The association between city of isolation and lineages was statistically significant; Haarlem and T lineages being higher in Kuala Lumpur (p<0.01). However, no statistically significant differences were noted when comparing drug resistance vs. major lineages, nor between gender and clades. Conclusions The ancestral East-African-Indian (EAI) lineage was most predominant followed by the Beijing lineage. A comparison of strains with those prevailing in neighboring countries in South Asia, East Asia and South East Asia underlined the phylogeographical specificity of SIT745 for Malaysia, and its probable ongoing evolution with locally evolved strains sharing a specific signature characterized by absence of spacers 37, 38, and 40. Pending complementary genotyping confirmation, we propose that SIT745/EAI-SOM is tentatively reclassified as SIT745/EAI-MYS. PMID:25502956

Prediction of microbe-disease association from the integration of neighbor and graph with collaborative recommendation model.

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing; Huang, Zhi-An; Zhang, Shanwen; Yan, Gui-Ying

2017-10-16

Accumulating clinical researches have shown that specific microbes with abnormal levels are closely associated with the development of various human diseases. Knowledge of microbe-disease associations can provide valuable insights for complex disease mechanism understanding as well as the prevention, diagnosis and treatment of various diseases. However, little effort has been made to predict microbial candidates for human complex diseases on a large scale. In this work, we developed a new computational model for predicting microbe-disease associations by combining two single recommendation methods. Based on the assumption that functionally similar microbes tend to get involved in the mechanism of similar disease, we adopted neighbor-based collaborative filtering and a graph-based scoring method to compute association possibility of microbe-disease pairs. The promising prediction performance could be attributed to the use of hybrid approach based on two single recommendation methods as well as the introduction of Gaussian kernel-based similarity and symptom-based disease similarity. To evaluate the performance of the proposed model, we implemented leave-one-out and fivefold cross validations on the HMDAD database, which is recently built as the first database collecting experimentally-confirmed microbe-disease associations. As a result, NGRHMDA achieved reliable results with AUCs of 0.9023 ± 0.0031 and 0.9111 in the validation frameworks of fivefold CV and LOOCV. In addition, 78.2% microbe samples and 66.7% disease samples are found to be consistent with the basic assumption of our work that microbes tend to get involved in the similar disease clusters, and vice versa. Compared with other methods, the prediction results yielded by NGRHMDA demonstrate its effective prediction performance for microbe-disease associations. It is anticipated that NGRHMDA can be used as a useful tool to search the most potential microbial candidates for various diseases, and therefore boosts the medical knowledge and drug development. The codes and dataset of our work can be downloaded from https://github.com/yahuang1991/NGRHMDA .

Media coverage of violent deaths in iraQ: an opportunistic capture-recapture assessment.

PubMed

Siegler, Anne; Roberts, Leslie; Balch, Erin; Bargues, Emmanuel; Bhalla, Asheesh; Bills, Corey; Dzeng, Elizabeth; Epelboym, Yan; Foster, Tory; Fulton, Latressa; Gallagher, Meghan; Gastolomendo, Juan David; Giorgi, Genessa; Habtehans, Semhar; Kim, Jennifer; McGee, Blake; McMahan, Andrew; Riese, Sara; Santamaria-Schwartz, Rachel; Walsh, Fiona; Wahlstrom, Jessica; Wedeles, John

2008-01-01

Western media coverage of the violence associated with the 2003 US-led invasion of Iraq has contrasted in magnitude and nature with population-based survey reports. The purpose of this study was to evaluate the extent to which first-hand reports of violent deaths were captured in the English language media by conducting in-depth interviews with Iraqi citizens. The England-based Iraq Body Count (IBC) has methodically monitored media reports and recorded each violent death in Iraq that could be confirmed by two English language media sources. Using the capture-recapture method, 25 Masters' Degree students were assigned to interview residents in Iraq and asked them to describe 10 violent deaths that occurred closest to their home since the 2003 invasion. Students then matched these reports with those documented in IBC. These reports were matched both individually and crosschecked in groups to obtain a percentage of those deaths captured in the English language media. Eighteen out of 25 students successfully interviewed someone in Iraq. Six contacted individuals by telephone, while the others conducted interviews via e-mail. One out of seven (14%) phone contacts refused to participate. Seventeen out of 18 primary interviewees resided in Baghdad, however, some interviewees reported deaths of neighbors that occurred while the neighbors were elsewhere. The Baghdad residents reported 161 deaths in total, 39 of which (24%) were believed to be reported in the press as summarized by IBC. An additional 13 deaths (8%) might have been in the database, and 61 (38%) were absolutely not in the database. The vast majority of violent deaths (estimated from the results of this study as being between 68-76%) are not reported by the press. Efforts to monitor events by press coverage or reports of tallies similar to those reported in the press, should be evaluated with the suspicion applied to any passive surveillance network: that it may be incomplete. Even in the most heavily reported conflicts, the media may miss the majority of violent events.

Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

NASA Astrophysics Data System (ADS)

Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

2016-03-01

The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

Improving phylogenetic analyses by incorporating additional information from genetic sequence databases.

PubMed

Liang, Li-Jung; Weiss, Robert E; Redelings, Benjamin; Suchard, Marc A

2009-10-01

Statistical analyses of phylogenetic data culminate in uncertain estimates of underlying model parameters. Lack of additional data hinders the ability to reduce this uncertainty, as the original phylogenetic dataset is often complete, containing the entire gene or genome information available for the given set of taxa. Informative priors in a Bayesian analysis can reduce posterior uncertainty; however, publicly available phylogenetic software specifies vague priors for model parameters by default. We build objective and informative priors using hierarchical random effect models that combine additional datasets whose parameters are not of direct interest but are similar to the analysis of interest. We propose principled statistical methods that permit more precise parameter estimates in phylogenetic analyses by creating informative priors for parameters of interest. Using additional sequence datasets from our lab or public databases, we construct a fully Bayesian semiparametric hierarchical model to combine datasets. A dynamic iteratively reweighted Markov chain Monte Carlo algorithm conveniently recycles posterior samples from the individual analyses. We demonstrate the value of our approach by examining the insertion-deletion (indel) process in the enolase gene across the Tree of Life using the phylogenetic software BALI-PHY; we incorporate prior information about indels from 82 curated alignments downloaded from the BAliBASE database.

Simultaneous detection of landmarks and key-frame in cardiac perfusion MRI using a joint spatial-temporal context model

NASA Astrophysics Data System (ADS)

Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens

2011-03-01

Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.

Initiation of a Database of CEUS Ground Motions for NGA East

NASA Astrophysics Data System (ADS)

Cramer, C. H.

2007-12-01

The Nuclear Regulatory Commission has funded the first stage of development of a database of central and eastern US (CEUS) broadband and accelerograph records, along the lines of the existing Next Generation Attenuation (NGA) database for active tectonic areas. This database will form the foundation of an NGA East project for the development of CEUS ground-motion prediction equations that include the effects of soils. This initial effort covers the development of a database design and the beginning of data collection to populate the database. It also includes some processing for important source parameters (Brune corner frequency and stress drop) and site parameters (kappa, Vs30). Besides collecting appropriate earthquake recordings and information, existing information about site conditions at recording sites will also be gathered, including geology and geotechnical information. The long-range goal of the database development is to complete the database and make it available in 2010. The database design is centered on CEUS ground motion information needs but is built on the Pacific Earthquake Engineering Research Center's (PEER) NGA experience. Documentation from the PEER NGA website was reviewed and relevant fields incorporated into the CEUS database design. CEUS database tables include ones for earthquake, station, component, record, and references. As was done for NGA, a CEUS ground- motion flat file of key information will be extracted from the CEUS database for use in attenuation relation development. A short report on the CEUS database and several initial design-definition files are available at https://umdrive.memphis.edu:443/xythoswfs/webui/_xy-7843974_docstore1. Comments and suggestions on the database design can be sent to the author. More details will be presented in a poster at the meeting.

Molecular formula and METLIN Personal Metabolite Database matching applied to the identification of compounds generated by LC/TOF-MS.

PubMed

Sana, Theodore R; Roark, Joseph C; Li, Xiangdong; Waddell, Keith; Fischer, Steven M

2008-09-01

In an effort to simplify and streamline compound identification from metabolomics data generated by liquid chromatography time-of-flight mass spectrometry, we have created software for constructing Personalized Metabolite Databases with content from over 15,000 compounds pulled from the public METLIN database (http://metlin.scripps.edu/). Moreover, we have added extra functionalities to the database that (a) permit the addition of user-defined retention times as an orthogonal searchable parameter to complement accurate mass data; and (b) allow interfacing to separate software, a Molecular Formula Generator (MFG), that facilitates reliable interpretation of any database matches from the accurate mass spectral data. To test the utility of this identification strategy, we added retention times to a subset of masses in this database, representing a mixture of 78 synthetic urine standards. The synthetic mixture was analyzed and screened against this METLIN urine database, resulting in 46 accurate mass and retention time matches. Human urine samples were subsequently analyzed under the same analytical conditions and screened against this database. A total of 1387 ions were detected in human urine; 16 of these ions matched both accurate mass and retention time parameters for the 78 urine standards in the database. Another 374 had only an accurate mass match to the database, with 163 of those masses also having the highest MFG score. Furthermore, MFG calculated a formula for a further 849 ions that had no match to the database. Taken together, these results suggest that the METLIN Personal Metabolite database and MFG software offer a robust strategy for confirming the formula of database matches. In the event of no database match, it also suggests possible formulas that may be helpful in interpreting the experimental results.

A neural network approach to cloud classification

NASA Technical Reports Server (NTRS)

Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.

1990-01-01

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

Reconstruction of ECG signals in presence of corruption.

PubMed

Ganeshapillai, Gartheeban; Liu, Jessica F; Guttag, John

2011-01-01

We present an approach to identifying and reconstructing corrupted regions in a multi-parameter physiological signal. The method, which uses information in correlated signals, is specifically designed to preserve clinically significant aspects of the signals. We use template matching to jointly segment the multi-parameter signal, morphological dissimilarity to estimate the quality of the signal segment, similarity search using features on a database of templates to find the closest match, and time-warping to reconstruct the corrupted segment with the matching template. In experiments carried out on the MIT-BIH Arrhythmia Database, a two-parameter database with many clinically significant arrhythmias, our method improved the classification accuracy of the beat type by more than 7 times on a signal corrupted with white Gaussian noise, and increased the similarity to the original signal, as measured by the normalized residual distance, by more than 2.5 times.

Evaluation of spectroscopic databases through radiative transfer simulations compared to observations. Application to the validation of GEISA 2015 with IASI and TCCON

NASA Astrophysics Data System (ADS)

Armante, Raymond; Scott, Noelle; Crevoisier, Cyril; Capelle, Virginie; Crepeau, Laurent; Jacquinet, Nicole; Chédin, Alain

2016-09-01

The quality of spectroscopic parameters that serve as input to forward radiative transfer models are essential to fully exploit remote sensing of Earth atmosphere. However, the process of updating spectroscopic databases in order to provide the users with a database that insures an optimal characterization of spectral properties of molecular absorption for radiative transfer modeling is challenging. The evaluation of the databases content and the underlying choices made by the managing team is thus a crucial step. Here, we introduce an original and powerful approach for evaluating spectroscopic parameters: the Spectroscopic Parameters And Radiative Transfer Evaluation (SPARTE) chain. The SPARTE chain relies on the comparison between forward radiative transfer simulations made by the 4A radiative transfer model and observations of spectra made from various observations collocated over several thousands of well-characterized atmospheric situations. Averaging the resulting 'calculated-observed spectral' residuals minimizes the random errors coming from both the radiometric noise of the instruments and the imperfect description of the atmospheric state. The SPARTE chain can be used to evaluate any spectroscopic databases, from the visible to the microwave, using any type of remote sensing observations (ground-based, airborne or space-borne). We show that the comparison of the shape of the residuals enables: (i) identifying incorrect line parameters (line position, intensity, width, pressure shift, etc.), even for molecules for which interferences between the lines have to be taken into account; (ii) proposing revised values, in cooperation with contributing teams; and (iii) validating the final updated parameters. In particular, we show that the simultaneous availability of two databases such as GEISA and HITRAN helps identifying remaining issues in each database. The SPARTE chain has been here applied to the validation of the update of GEISA-2015 in 2 spectral regions of particular interest for several currently exploited or planned Earth space missions: the thermal infrared domain and the short-wave infrared domain, for which observations from the space-borne IASI instrument and from the ground-based FTS instruments at the Parkfalls TCCON site are used respectively. Main results include: (i) the validation of the positions and intensities of line parameters, with overall significantly lower residuals for GEISA-2015 than for GEISA-2011 and (iii) the validation of the choice made on the parameters (such as pressure shift and air-broadened width) which has not been given by the provider but completed by ourselves. For example, comparisons between residuals obtained with GEISA-2015 and HITRAN-2012 have highlighted a specific issue with some HWHM values in the latter that can be clearly identified on the 'calculated-observed' residuals.

Space flight risk data collection and analysis project: Risk and reliability database

NASA Technical Reports Server (NTRS)

1994-01-01

The focus of the NASA 'Space Flight Risk Data Collection and Analysis' project was to acquire and evaluate space flight data with the express purpose of establishing a database containing measurements of specific risk assessment - reliability - availability - maintainability - supportability (RRAMS) parameters. The developed comprehensive RRAMS database will support the performance of future NASA and aerospace industry risk and reliability studies. One of the primary goals has been to acquire unprocessed information relating to the reliability and availability of launch vehicles and the subsystems and components thereof from the 45th Space Wing (formerly Eastern Space and Missile Command -ESMC) at Patrick Air Force Base. After evaluating and analyzing this information, it was encoded in terms of parameters pertinent to ascertaining reliability and availability statistics, and then assembled into an appropriate database structure.

Active fault databases: building a bridge between earthquake geologists and seismic hazard practitioners, the case of the QAFI v.3 database

NASA Astrophysics Data System (ADS)

García-Mayordomo, Julián; Martín-Banda, Raquel; Insua-Arévalo, Juan M.; Álvarez-Gómez, José A.; Martínez-Díaz, José J.; Cabral, João

2017-08-01

Active fault databases are a very powerful and useful tool in seismic hazard assessment, particularly when singular faults are considered seismogenic sources. Active fault databases are also a very relevant source of information for earth scientists, earthquake engineers and even teachers or journalists. Hence, active fault databases should be updated and thoroughly reviewed on a regular basis in order to keep a standard quality and uniformed criteria. Desirably, active fault databases should somehow indicate the quality of the geological data and, particularly, the reliability attributed to crucial fault-seismic parameters, such as maximum magnitude and recurrence interval. In this paper we explain how we tackled these issues during the process of updating and reviewing the Quaternary Active Fault Database of Iberia (QAFI) to its current version 3. We devote particular attention to describing the scheme devised for classifying the quality and representativeness of the geological evidence of Quaternary activity and the accuracy of the slip rate estimation in the database. Subsequently, we use this information as input for a straightforward rating of the level of reliability of maximum magnitude and recurrence interval fault seismic parameters. We conclude that QAFI v.3 is a much better database than version 2 either for proper use in seismic hazard applications or as an informative source for non-specialized users. However, we already envision new improvements for a future update.

A retrieval algorithm of hydrometer profile for submillimeter-wave radiometer

NASA Astrophysics Data System (ADS)

Liu, Yuli; Buehler, Stefan; Liu, Heguang

2017-04-01

Vertical profiles of particle microphysics perform vital functions for the estimation of climatic feedback. This paper proposes a new algorithm to retrieve the profile of the parameters of the hydrometeor(i.e., ice, snow, rain, liquid cloud, graupel) based on passive submillimeter-wave measurements. These parameters include water content and particle size. The first part of the algorithm builds the database and retrieves the integrated quantities. Database is built up by Atmospheric Radiative Transfer Simulator(ARTS), which uses atmosphere data to simulate the corresponding brightness temperature. Neural network, trained by the precalculated database, is developed to retrieve the water path for each type of particles. The second part of the algorithm analyses the statistical relationship between water path and vertical parameters profiles. Based on the strong dependence existing between vertical layers in the profiles, Principal Component Analysis(PCA) technique is applied. The third part of the algorithm uses the forward model explicitly to retrieve the hydrometeor profiles. Cost function is calculated in each iteration, and Differential Evolution(DE) algorithm is used to adjust the parameter values during the evolutionary process. The performance of this algorithm is planning to be verified for both simulation database and measurement data, by retrieving profiles in comparison with the initial one. Results show that this algorithm has the ability to retrieve the hydrometeor profiles efficiently. The combination of ARTS and optimization algorithm can get much better results than the commonly used database approach. Meanwhile, the concept that ARTS can be used explicitly in the retrieval process shows great potential in providing solution to other retrieval problems.

dbAMEPNI: a database of alanine mutagenic effects for protein–nucleic acid interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Ling; Xiong, Yi; Gao, Hongyun

Protein–nucleic acid interactions play essential roles in various biological activities such as gene regulation, transcription, DNA repair and DNA packaging. Understanding the effects of amino acid substitutions on protein–nucleic acid binding affinities can help elucidate the molecular mechanism of protein–nucleic acid recognition. Until now, no comprehensive and updated database of quantitative binding data on alanine mutagenic effects for protein–nucleic acid interactions is publicly accessible. Thus, we developed a new database of Alanine Mutagenic Effects for Protein-Nucleic Acid Interactions (dbAMEPNI). dbAMEPNI is a manually curated, literature-derived database, comprising over 577 alanine mutagenic data with experimentally determined binding affinities for protein–nucleic acidmore » complexes. Here, it contains several important parameters, such as dissociation constant (Kd), Gibbs free energy change (ΔΔG), experimental conditions and structural parameters of mutant residues. In addition, the database provides an extended dataset of 282 single alanine mutations with only qualitative data (or descriptive effects) of thermodynamic information.« less

DABAM: an open-source database of X-ray mirrors metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele

2016-04-20

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper,more » with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. Some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.« less

DABAM: an open-source database of X-ray mirrors metrology

PubMed Central

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele; Glass, Mark; Idir, Mourad; Metz, Jim; Raimondi, Lorenzo; Rebuffi, Luca; Reininger, Ruben; Shi, Xianbo; Siewert, Frank; Spielmann-Jaeggi, Sibylle; Takacs, Peter; Tomasset, Muriel; Tonnessen, Tom; Vivo, Amparo; Yashchuk, Valeriy

2016-01-01

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper, with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. Some optics simulations are presented and discussed to illustrate the real use of the profiles from the database. PMID:27140145

dbAMEPNI: a database of alanine mutagenic effects for protein–nucleic acid interactions

DOE PAGES

Liu, Ling; Xiong, Yi; Gao, Hongyun; ...

2018-04-02

Protein–nucleic acid interactions play essential roles in various biological activities such as gene regulation, transcription, DNA repair and DNA packaging. Understanding the effects of amino acid substitutions on protein–nucleic acid binding affinities can help elucidate the molecular mechanism of protein–nucleic acid recognition. Until now, no comprehensive and updated database of quantitative binding data on alanine mutagenic effects for protein–nucleic acid interactions is publicly accessible. Thus, we developed a new database of Alanine Mutagenic Effects for Protein-Nucleic Acid Interactions (dbAMEPNI). dbAMEPNI is a manually curated, literature-derived database, comprising over 577 alanine mutagenic data with experimentally determined binding affinities for protein–nucleic acidmore » complexes. Here, it contains several important parameters, such as dissociation constant (Kd), Gibbs free energy change (ΔΔG), experimental conditions and structural parameters of mutant residues. In addition, the database provides an extended dataset of 282 single alanine mutations with only qualitative data (or descriptive effects) of thermodynamic information.« less

DABAM: An open-source database of X-ray mirrors metrology

DOE PAGES

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele; ...

2016-05-01

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper,more » with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. In conclusion, some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.« less

DABAM: an open-source database of X-ray mirrors metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper,more » with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. Some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.« less

DABAM: An open-source database of X-ray mirrors metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper,more » with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. In conclusion, some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.« less

Effects of energy transfer on quantum efficiency of YAG:Nd

NASA Astrophysics Data System (ADS)

Lupei, V.; Lupei, A.; Georgescu, S.; Yen, W. M.

1989-10-01

Using the energy transfer parameters deduced from the study on nonexponential luminescence decay of the 4F3/2 level of Nd(3+) in YAG at room temperature, it is shown that up to 1.5 at. pct Nd, the relative quantum efficiency is reduced by an amount of 18.2C, C being the relative Nd concentration. It is pointed out that about 20 percent of this reduction is due to a very effective quenching mechanism inside the nearest-neighbor Nd-ion pairs.

Effect of Fourier transform on the streaming in quantum lattice gas algorithms

NASA Astrophysics Data System (ADS)

Oganesov, Armen; Vahala, George; Vahala, Linda; Soe, Min

2018-04-01

All our previous quantum lattice gas algorithms for nonlinear physics have approximated the kinetic energy operator by streaming sequences to neighboring lattice sites. Here, the kinetic energy can be treated to all orders by Fourier transforming the kinetic energy operator with interlaced Dirac-based unitary collision operators. Benchmarking against exact solutions for the 1D nonlinear Schrodinger equation shows an extended range of parameters (soliton speeds and amplitudes) over the Dirac-based near-lattice-site streaming quantum algorithm.

Flocking of the Motsch-Tadmor Model with a Cut-Off Interaction Function

NASA Astrophysics Data System (ADS)

Jin, Chunyin

2018-04-01

In this paper, we study the flocking behavior of the Motsch-Tadmor model with a cut-off interaction function. Our analysis shows that connectedness is important for flocking of this kind of model. Fortunately, we get a sufficient condition imposed only on the model parameters and initial data to guarantee the connectedness of the neighbor graph associated with the system. Then we present a theoretical analysis for flocking, and show that the system achieves consensus at an exponential rate.

Spectrum, symmetries, and dynamics of Heisenberg spin-1/2 chains

NASA Astrophysics Data System (ADS)

Joel, Kira; Kollmar, Davida; Santos, Lea

2013-03-01

Quantum spin chains are prototype quantum many-body systems. They are employed in the description of various complex physical phenomena. Here we provide an introduction to the subject by focusing on the time evolution of Heisenberg spin-1/2 chains with couplings between nearest-neighbor sites only. We study how the anisotropy parameter and the symmetries of the model affect its time evolution. Our predictions are based on the analysis of the eigenvalues and eigenstates of the system and then confirmed with actual numerical results.

Adult and Child Semantic Neighbors of the Kroll and Potter (1984) Nonobjects

PubMed Central

Storkel, Holly L.; Adlof, Suzanne M.

2008-01-01

Purpose The purpose was to determine the number of semantic neighbors, namely semantic set size, for 88 nonobjects (Kroll & Potter, 1984) and determine how semantic set size related to other measures and age. Method Data were collected from 82 adults and 92 preschool children in a discrete association task. The nonobjects were presented via computer, and participants reported the first word that came to mind that was meaningfully related to the nonobject. Words reported by two or more participants were considered semantic neighbors. The strength of each neighbor was computed as the proportion of participants who reported the neighbor. Results Results showed that semantic set size was not significantly correlated with objectlikeness ratings or object decision reaction times from Kroll and Potter (1984). However, semantic set size was significantly negatively correlated with the strength of the strongest neighbor(s). In terms of age effects, adult and child semantic set sizes were significantly positively correlated and the majority of numeric differences were on the order of 0–3 neighbors. Comparison of actual neighbors showed greater discrepancies; however, this varied by neighbor strength. Conclusions Semantic set size can be determined for nonobjects. Specific guidelines are suggested for using these nonobjects in future research. PMID:19252127

Continuity and Change in Relationships with Neighbors: Implications for Psychological Well-being in Middle and Later Life

PubMed Central

Reyes, Laurent

2015-01-01

Objectives. There is growing enthusiasm for community initiatives that aim to strengthen neighbor relationships to promote well-being in later life. Nevertheless, few studies have examined the extent to which relationships with neighbors are associated with better psychological well-being among midlife and older adults. Methods. We used data from 1,071 noninstitutionalized, English-speaking adults, aged 40–70 years, who participated in both waves of the 1995–2005 National Survey of Midlife Development in the United States. Lagged dependent regression models were estimated to examine associations between changes in two dimensions of neighbor relationships (contact and perceived support) and psychological well-being. Results. Few associations were found between relationships with neighbors and negative or positive affect. In contrast, having continuously low levels of contact with neighbors, or losing contact with neighbors over the 10-year study period, was associated with declining levels of eudaimonic well-being. Associations between contact and this aspect of well-being were explained, in part, by less perceived support from neighbors. Discussion. Results suggest that continuity and change in relationships with neighbors is especially important for more developmental aspects of psychological well-being. Implications for future research on the meaning of neighbor relationships and aging in community are discussed. PMID:25106785

Photosynthesis-irradiance parameters of marine phytoplankton: synthesis of a global data set

NASA Astrophysics Data System (ADS)

Bouman, Heather A.; Platt, Trevor; Doblin, Martina; Figueiras, Francisco G.; Gudmundsson, Kristinn; Gudfinnsson, Hafsteinn G.; Huang, Bangqin; Hickman, Anna; Hiscock, Michael; Jackson, Thomas; Lutz, Vivian A.; Mélin, Frédéric; Rey, Francisco; Pepin, Pierre; Segura, Valeria; Tilstone, Gavin H.; van Dongen-Vogels, Virginie; Sathyendranath, Shubha

2018-02-01

The photosynthetic performance of marine phytoplankton varies in response to a variety of factors, environmental and taxonomic. One of the aims of the MArine primary Production: model Parameters from Space (MAPPS) project of the European Space Agency is to assemble a global database of photosynthesis-irradiance (P-E) parameters from a range of oceanographic regimes as an aid to examining the basin-scale variability in the photophysiological response of marine phytoplankton and to use this information to improve the assignment of P-E parameters in the estimation of global marine primary production using satellite data. The MAPPS P-E database, which consists of over 5000 P-E experiments, provides information on the spatio-temporal variability in the two P-E parameters (the assimilation number, PmB, and the initial slope, αB, where the superscripts B indicate normalisation to concentration of chlorophyll) that are fundamental inputs for models (satellite-based and otherwise) of marine primary production that use chlorophyll as the state variable. Quality-control measures consisted of removing samples with abnormally high parameter values and flags were added to denote whether the spectral quality of the incubator lamp was used to calculate a broad-band value of αB. The MAPPS database provides a photophysiological data set that is unprecedented in number of observations and in spatial coverage. The database will be useful to a variety of research communities, including marine ecologists, biogeochemical modellers, remote-sensing scientists and algal physiologists. The compiled data are available at https://doi.org/10.1594/PANGAEA.874087 (Bouman et al., 2017).

Physical re-examination of parameters on a molecular collisions-based diffusion model for diffusivity prediction in polymers.

PubMed

Ohashi, Hidenori; Tamaki, Takanori; Yamaguchi, Takeo

2011-12-29

Molecular collisions, which are the microscopic origin of molecular diffusive motion, are affected by both the molecular surface area and the distance between molecules. Their product can be regarded as the free space around a penetrant molecule defined as the "shell-like free volume" and can be taken as a characteristic of molecular collisions. On the basis of this notion, a new diffusion theory has been developed. The model can predict molecular diffusivity in polymeric systems using only well-defined single-component parameters of molecular volume, molecular surface area, free volume, and pre-exponential factors. By consideration of the physical description of the model, the actual body moved and which neighbor molecules are collided with are the volume and the surface area of the penetrant molecular core. In the present study, a semiempirical quantum chemical calculation was used to calculate both of these parameters. The model and the newly developed parameters offer fairly good predictive ability. © 2011 American Chemical Society

Effect of the curvature parameter on least-squares prediction within poor data coverage: case study for Africa

NASA Astrophysics Data System (ADS)

Abd-Elmotaal, Hussein; Kühtreiber, Norbert

2016-04-01

In the framework of the IAG African Geoid Project, there are a lot of large data gaps in its gravity database. These gaps are filled initially using unequal weight least-squares prediction technique. This technique uses a generalized Hirvonen covariance function model to replace the empirically determined covariance function. The generalized Hirvonen covariance function model has a sensitive parameter which is related to the curvature parameter of the covariance function at the origin. This paper studies the effect of the curvature parameter on the least-squares prediction results, especially in the large data gaps as appearing in the African gravity database. An optimum estimation of the curvature parameter has also been carried out. A wide comparison among the results obtained in this research along with their obtained accuracy is given and thoroughly discussed.

Creation of Frustrated Systems by d-dot Array

NASA Astrophysics Data System (ADS)

Masahiko, Machida

2004-03-01

When a square shape dot of High-Tc superconductor is embedded in s-wave superconducting matrix, half quantized vortices are spontaneously generated at the corners of the dot. This feature gives the magnetic interactions between neighboring dots in array systems composed of sevaral dots of High-Tc superconductor and allows us to make magnetic interaction systems. We propose that we can create interesting frustrated systems like the spin-ice by setting the dots in various manners. In order to demonstrate which types of frustrated systems are possible, we perform numerical simulations for the time-dependent Ginzburg-Landau equation describing dynamics of the superconducting order parameters with d-wave and s-wave symmetries. The simulations reveal that the proposed system has two parameters originated from the magnetic interaction between emerged half vortices. We tune the parameters and show various patterns of half vortices from the Ising to the ice model.

Control of DNA-Functionalized Nanoparticle Assembly

NASA Astrophysics Data System (ADS)

Olvera de La Cruz, Monica

Directed crystallization of a large variety of nanoparticles, including proteins, via DNA hybridization kinetics has led to unique materials with a broad range of crystal symmetries. The nanoparticles are functionalized with DNA chains that link neighboring functionalized units. The shape of the nanoparticle, the DNA length, the sequence of the hybridizing DNA linker and the grafting density determine the crystal symmetries and lattice spacing. By carefully selecting these parameters one can, in principle, achieve all the symmetries found for both atomic and colloidal crystals of asymmetric shapes as well as new symmetries, and drive transitions between them. A scale-accurate coarse-grained model with explicit DNA chains provides the design parameters, including degree of hybridization, to achieve specific crystal structures. The model also provides surface energy values to determine the shape of defect-free single crystals with macroscopic anisotropic properties, as well as the parameters to develop colloidal models that reproduce both the shape of single crystals and their growth kinetics.

Aggregation-fragmentation-diffusion model for trail dynamics

DOE PAGES

Kawagoe, Kyle; Huber, Greg; Pradas, Marc; ...

2017-07-21

We investigate statistical properties of trails formed by a random process incorporating aggregation, fragmentation, and diffusion. In this stochastic process, which takes place in one spatial dimension, two neighboring trails may combine to form a larger one, and also one trail may split into two. In addition, trails move diffusively. The model is defined by two parameters which quantify the fragmentation rate and the fragment size. In the long-time limit, the system reaches a steady state, and our focus is the limiting distribution of trail weights. We find that the density of trail weight has power-law tail P(w)~w –γ formore » small weight w. We obtain the exponent γ analytically and find that it varies continuously with the two model parameters. In conclusion, the exponent γ can be positive or negative, so that in one range of parameters small-weight trails are abundant and in the complementary range they are rare.« less

Competing phases, phase separation, and coexistence in the extended one-dimensional bosonic Hubbard model

DOE PAGES

Batrouni, G. G.; Rousseau, V. G.; Scalettar, R. T.; ...

2014-11-17

Here, we study the phase diagram of the one-dimensional bosonic Hubbard model with contact (U) and near neighbor (V ) interactions focusing on the gapped Haldane insulating (HI) phase which is characterized by an exotic nonlocal order parameter. The parameter regime (U, V and μ) where this phase exists and how it competes with other phases such as the supersolid (SS) phase, is incompletely understood. We use the Stochastic Green Function quantum Monte Carlo algorithm as well as the density matrix renormalization group to map out the phase diagram. The HI exists only at = 1, the SS phase existsmore » for a very wide range of parameters (including commensurate fillings) and displays power law decay in the one body Green function were our main conclusions. Additionally, we show that at fixed integer density, the system exhibits phase separation in the (U, V ) plane.« less

Random close packing of polydisperse jammed emulsions

NASA Astrophysics Data System (ADS)

Brujic, Jasna

2010-03-01

Packing problems are everywhere, ranging from oil extraction through porous rocks to grain storage in silos and the compaction of pharmaceutical powders into tablets. At a given density, particulate systems pack into a mechanically stable and amorphous jammed state. Theoretical frameworks have proposed a connection between this jammed state and the glass transition, a thermodynamics of jamming, as well as geometric modeling of random packings. Nevertheless, a simple underlying mechanism for the random assembly of athermal particles, analogous to crystalline ordering, remains unknown. Here we use 3D measurements of polydisperse packings of emulsion droplets to build a simple statistical model in which the complexity of the global packing is distilled into a local stochastic process. From the perspective of a single particle the packing problem is reduced to the random formation of nearest neighbors, followed by a choice of contacts among them. The two key parameters in the model, the available space around a particle and the ratio of contacts to neighbors, are directly obtained from experiments. Remarkably, we demonstrate that this ``granocentric'' view captures the properties of the polydisperse emulsion packing, ranging from the microscopic distributions of nearest neighbors and contacts to local density fluctuations and all the way to the global packing density. Further applications to monodisperse and bidisperse systems quantitatively agree with previously measured trends in global density. This model therefore reveals a general principle of organization for random packing and lays the foundations for a theory of jammed matter.

Influence of neighboring adherent cells on laminar flow induced shear stress in vitro—A systematic study

PubMed Central

Djukelic, Mario; Westerhausen, Christoph

2017-01-01

Cells experience forces if subjected to laminar flow. These forces, mostly of shear force character, are strongly dependent not only on the applied flow field itself but also on hydrodynamic effects originating from neighboring cells. This particularly becomes important for the interpretation of data from in vitro experiments in flow chambers without confluent cell layers. By employing numerical Finite Element Method simulations of such assemblies of deformable objects under shear flow, we investigate the occurring stress within elastic adherent cells and the influence of neighboring cells on these quantities. For this, we simulate single and multiple adherent cells of different shapes fixed on a solid substrate under laminar flow parallel to the substrate for different velocities. We determine the local stress within the cells close to the cell-substrate-interface and the overall stress of the cells by surface integration over the cell surface. Comparing each measurand in the case of a multiple cell situation with the corresponding one of single cells under identical conditions, we introduce a dimensionless influence factor. The systematic variation of the distance and angle between cells, where the latter is with respect to the flow direction, flow velocity, Young's modulus, cell shape, and cell number, enables us to describe the actual influence on a cell. Overall, we here demonstrate that the cell density is a crucial parameter for all studies on flow induced experiments on adherent cells in vitro. PMID:28798851

Modeling the dynamics of dissent

NASA Astrophysics Data System (ADS)

Lee, Eun; Holme, Petter; Lee, Sang Hoon

2017-11-01

We investigate the formation of opinion against authority in an authoritarian society composed of agents with different levels of authority. We explore a ;dissenting; opinion, held by lower-ranking, obedient, or less authoritative people, spreading in an environment of an ;affirmative; opinion held by authoritative leaders. A real-world example would be a corrupt society where people revolt against such leaders, but it can be applied to more general situations. In our model, agents can change their opinion depending on their authority relative to their neighbors and their own confidence level. In addition, with a certain probability, agents can override the affirmative opinion to take the dissenting opinion of a neighbor. Based on analytic derivation and numerical simulations, we observe that both the network structure and heterogeneity in authority, and their correlation, significantly affect the possibility of the dissenting opinion to spread through the population. In particular, the dissenting opinion is suppressed when the authority distribution is very heterogeneous and there exists a positive correlation between the authority and the number of neighbors of people (degree). Except for such an extreme case, though, spreading of the dissenting opinion takes place when people have the tendency to override the authority to hold the dissenting opinion, but the dissenting opinion can take a long time to spread to the entire society, depending on the model parameters. We argue that the internal social structure of agents sets the scale of the time to reach consensus, based on the analysis of the underlying structural properties of opinion spreading.

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

NASA Astrophysics Data System (ADS)

Thompson, A. P.; Swiler, L. P.; Trott, C. R.; Foiles, S. M.; Tucker, G. J.

2015-03-01

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

Thermal contact through a two-temperature kinetic Ising chain

NASA Astrophysics Data System (ADS)

Bauer, M.; Cornu, F.

2018-05-01

We consider a model for thermal contact through a diathermal interface between two macroscopic bodies at different temperatures: an Ising spin chain with nearest neighbor interactions is endowed with a Glauber dynamics with different temperatures and kinetic parameters on alternating sites. The inhomogeneity of the kinetic parameter is a novelty with respect to the model of Racz and Zia (1994 Phys. Rev. E 49 139), and we exhibit its influence upon the stationary non equilibrium values of the two-spin correlations at any distance. By mapping to the dynamics of spin domain walls and using free fermion techniques, we determine the scaled generating function for the cumulants of the exchanged heat amounts per unit of time in the long time limit.

A classification scheme for edge-localized modes based on their probability distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shabbir, A., E-mail: aqsa.shabbir@ugent.be; Max Planck Institute for Plasma Physics, D-85748 Garching; Hornung, G.

We present here an automated classification scheme which is particularly well suited to scenarios where the parameters have significant uncertainties or are stochastic quantities. To this end, the parameters are modeled with probability distributions in a metric space and classification is conducted using the notion of nearest neighbors. The presented framework is then applied to the classification of type I and type III edge-localized modes (ELMs) from a set of carbon-wall plasmas at JET. This provides a fast, standardized classification of ELM types which is expected to significantly reduce the effort of ELM experts in identifying ELM types. Further, themore » classification scheme is general and can be applied to various other plasma phenomena as well.« less

Impact of line parameter database, continuum absorption, full grind configuration, and L1B update on GOSAT TIR methane retrieval

NASA Astrophysics Data System (ADS)

Yamada, A.; Saitoh, N.; Nonogaki, R.; Imasu, R.; Shiomi, K.; Kuze, A.

2016-12-01

The thermal infrared (TIR) band of Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT) observes CH4 profile at wavenumber range from 1210 cm-1 to 1360 cm-1 including CH4 ν4 band. The current retrieval algorithm (V1.0) uses LBLRTM V12.1 with AER V3.1 line database to calculate optical depth. LBLRTM V12.1 include MT_CKD 2.5.2 model to calculate continuum absorption. The continuum absorption has large uncertainty, especially temperature dependent coefficient, between BPS model and MT_CKD model in the wavenumber region of 1210-1250 cm-1(Paynter and Ramaswamy, 2014). The purpose of this study is to assess the impact on CH4 retrieval from the line parameter databases and the uncertainty of continuum absorption. We used AER v1.0 database, HITRAN2004 database, HITRAN2008 database, AER V3.2 database, and HITRAN2012 database (Rothman et al. 2005, 2009, and 2013. Clough et al., 2005). AER V1.0 database is based on HITRAN2000. The CH4 line parameters of AER V3.1 and V3.2 databases are developed from HITRAN2008 including updates until May 2009 with line mixing parameters. We compared the retrieved CH4 with the HIPPO CH4 observation (Wofsy et al., 2012). The difference of AER V3.2 was the smallest and 24.1 ± 45.9 ppbv. The differences of AER V1.0, HITRAN2004, HITRAN2008, and HITRAN2012 were 35.6 ± 46.5 ppbv, 37.6 ± 46.3 ppbv, 32.1 ± 46.1 ppbv, and 35.2 ± 46.0 ppbv, respectively. Compare AER V3.2 case to HITRAN2008 case, the line coupling effect reduced difference by 8.0 ppbv. Median values of Residual difference from HITRAN2008 to AER V1.0, HITRAN2004, AER V3.2, and HITRAN2012 were 0.6 K, 0.1 K, -0.08 K, and 0.08 K, respectively, while median values of transmittance difference were less than 0.0003 and transmittance differences have small wavenumber dependence. We also discuss the retrieval error from the uncertainty of the continuum absorption, the test of full grid configuration for retrieval, and the retrieval results using GOSAT TIR L1B V203203, which are sample products to evaluate the next level 1B algorithm.

A scientific database for real-time Neutron Monitor measurements - taking Neutron Monitors into the 21st century

NASA Astrophysics Data System (ADS)

Steigies, Christian

2012-07-01

The Neutron Monitor Database project, www.nmdb.eu, has been funded in 2008 and 2009 by the European Commission's 7th framework program (FP7). Neutron monitors (NMs) have been in use worldwide since the International Geophysical Year (IGY) in 1957 and cosmic ray data from the IGY and the improved NM64 NMs has been distributed since this time, but a common data format existed only for data with one hour resolution. This data was first distributed in printed books, later via the World Data Center ftp server. In the 1990's the first NM stations started to record data at higher resolutions (typically 1 minute) and publish in on their webpages. However, every NM station chose their own format, making it cumbersome to work with this distributed data. In NMDB all European and some neighboring NM stations came together to agree on a common format for high-resolution data and made this available via a centralized database. The goal of NMDB is to make all data from all NM stations available in real-time. The original NMDB network has recently been joined by the Bartol Research Institute (Newark DE, USA), the National Autonomous University of Mexico and the North-West University (Potchefstroom, South Africa). The data is accessible to everyone via an easy to use webinterface, but expert users can also directly access the database to build applications like real-time space weather alerts. Even though SQL databases are used today by most webservices (blogs, wikis, social media, e-commerce), the power of an SQL database has not yet been fully realized by the scientific community. In training courses, we are teaching how to make use of NMDB, how to join NMDB, and how to ensure the data quality. The present status of the extended NMDB will be presented. The consortium welcomes further data providers to help increase the scientific contributions of the worldwide neutron monitor network to heliospheric physics and space weather.

The sound of enemies and friends in the neighborhood.

PubMed

Pecher, Diane; Boot, Inge; van Dantzig, Saskia; Madden, Carol J; Huber, David E; Zeelenberg, René

2011-01-01

Previous studies (e.g., Pecher, Zeelenberg, & Wagenmakers, 2005) found that semantic classification performance is better for target words with orthographic neighbors that are mostly from the same semantic class (e.g., living) compared to target words with orthographic neighbors that are mostly from the opposite semantic class (e.g., nonliving). In the present study we investigated the contribution of phonology to orthographic neighborhood effects by comparing effects of phonologically congruent orthographic neighbors (book-hook) to phonologically incongruent orthographic neighbors (sand-wand). The prior presentation of a semantically congruent word produced larger effects on subsequent animacy decisions when the previously presented word was a phonologically congruent neighbor than when it was a phonologically incongruent neighbor. In a second experiment, performance differences between target words with versus without semantically congruent orthographic neighbors were larger if the orthographic neighbors were also phonologically congruent. These results support models of visual word recognition that assume an important role for phonology in cascaded access to meaning.

Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search.

PubMed

Liu, Xianglong; Deng, Cheng; Lang, Bo; Tao, Dacheng; Li, Xuelong

2016-02-01

Recent years have witnessed the success of binary hashing techniques in approximate nearest neighbor search. In practice, multiple hash tables are usually built using hashing to cover more desired results in the hit buckets of each table. However, rare work studies the unified approach to constructing multiple informative hash tables using any type of hashing algorithms. Meanwhile, for multiple table search, it also lacks of a generic query-adaptive and fine-grained ranking scheme that can alleviate the binary quantization loss suffered in the standard hashing techniques. To solve the above problems, in this paper, we first regard the table construction as a selection problem over a set of candidate hash functions. With the graph representation of the function set, we propose an efficient solution that sequentially applies normalized dominant set to finding the most informative and independent hash functions for each table. To further reduce the redundancy between tables, we explore the reciprocal hash tables in a boosting manner, where the hash function graph is updated with high weights emphasized on the misclassified neighbor pairs of previous hash tables. To refine the ranking of the retrieved buckets within a certain Hamming radius from the query, we propose a query-adaptive bitwise weighting scheme to enable fine-grained bucket ranking in each hash table, exploiting the discriminative power of its hash functions and their complement for nearest neighbor search. Moreover, we integrate such scheme into the multiple table search using a fast, yet reciprocal table lookup algorithm within the adaptive weighted Hamming radius. In this paper, both the construction method and the query-adaptive search method are general and compatible with different types of hashing algorithms using different feature spaces and/or parameter settings. Our extensive experiments on several large-scale benchmarks demonstrate that the proposed techniques can significantly outperform both the naive construction methods and the state-of-the-art hashing algorithms.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

PubMed

Azman, Syafiq Kamarul; Anwar, Muhammad Zohaib; Henschel, Andreas

2017-07-24

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Near-Neighbor Algorithms for Processing Bearing Data

DTIC Science & Technology

1989-05-10

neighbor algorithms need not be universally more cost -effective than brute force methods. While the data access time of near-neighbor techniques scales with...the number of objects N better than brute force, the cost of setting up the data structure could scale worse than (Continues) 20...for the near neighbors NN2 1 (i). Depending on the particular NN algorithm, the cost of accessing near neighbors for each ai E S1 scales as either N

Enhancing and Archiving the APS Catalog of the POSS I

NASA Technical Reports Server (NTRS)

Humphreys, Roberta M.

2003-01-01

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

A sequence database allowing automated genotyping of Classical swine fever virus isolates.

PubMed

Dreier, Sabrina; Zimmermann, Bernd; Moennig, Volker; Greiser-Wilke, Irene

2007-03-01

Classical swine fever (CSF) is a highly contagious viral disease of pigs. According to the OIE classification of diseases it is classified as a notifiable (previously List A) disease, thus having the potential for causing severe socio-economic problems and affecting severely the international trade of pigs and pig products. Effective control measures are compulsory, and to expose weaknesses a reliable tracing of the spread of the virus is necessary. Genetic typing has proved to be the method of choice. However, genotyping involves the use of multiple software applications, which is laborious and complex. The implementation of a sequence database, which is accessible by the World Wide Web with the option to type automatically new CSF virus isolates once the sequence is available is described. The sequence to be typed is tested for correct orientation and, if necessary, adjusted to the right length. The alignment and the neighbor-joining phylogenetic analysis with a standard set of sequences can then be calculated. The results are displayed as a graph. As an example, the determination is shown of the genetic subgroup of the isolate obtained from the outbreaks registered in Russia, in 2005. After registration (Irene.greiser-wilke@tiho-hannover.de) the database including the module for genotyping are accessible under http://viro08.tiho-hannover.de/eg/eurl_virus_db.htm.

Diagnostic tools for nearest neighbors techniques when used with satellite imagery

Treesearch

Ronald E. McRoberts

2009-01-01

Nearest neighbors techniques are non-parametric approaches to multivariate prediction that are useful for predicting both continuous and categorical forest attribute variables. Although some assumptions underlying nearest neighbor techniques are common to other prediction techniques such as regression, other assumptions are unique to nearest neighbor techniques....

Normal values and standardization of parameters in nuclear cardiology: Japanese Society of Nuclear Medicine working group database.

PubMed

Nakajima, Kenichi; Matsumoto, Naoya; Kasai, Tokuo; Matsuo, Shinro; Kiso, Keisuke; Okuda, Koichi

2016-04-01

As a 2-year project of the Japanese Society of Nuclear Medicine working group activity, normal myocardial imaging databases were accumulated and summarized. Stress-rest with gated and non-gated image sets were accumulated for myocardial perfusion imaging and could be used for perfusion defect scoring and normal left ventricular (LV) function analysis. For single-photon emission computed tomography (SPECT) with multi-focal collimator design, databases of supine and prone positions and computed tomography (CT)-based attenuation correction were created. The CT-based correction provided similar perfusion patterns between genders. In phase analysis of gated myocardial perfusion SPECT, a new approach for analyzing dyssynchrony, normal ranges of parameters for phase bandwidth, standard deviation and entropy were determined in four software programs. Although the results were not interchangeable, dependency on gender, ejection fraction and volumes were common characteristics of these parameters. Standardization of (123)I-MIBG sympathetic imaging was performed regarding heart-to-mediastinum ratio (HMR) using a calibration phantom method. The HMRs from any collimator types could be converted to the value with medium-energy comparable collimators. Appropriate quantification based on common normal databases and standard technology could play a pivotal role for clinical practice and researches.

A theoretical-electron-density databank using a model of real and virtual spherical atoms.

PubMed

Nassour, Ayoub; Domagala, Slawomir; Guillot, Benoit; Leduc, Theo; Lecomte, Claude; Jelsch, Christian

2017-08-01

A database describing the electron density of common chemical groups using combinations of real and virtual spherical atoms is proposed, as an alternative to the multipolar atom modelling of the molecular charge density. Theoretical structure factors were computed from periodic density functional theory calculations on 38 crystal structures of small molecules and the charge density was subsequently refined using a density model based on real spherical atoms and additional dummy charges on the covalent bonds and on electron lone-pair sites. The electron-density parameters of real and dummy atoms present in a similar chemical environment were averaged on all the molecules studied to build a database of transferable spherical atoms. Compared with the now-popular databases of transferable multipolar parameters, the spherical charge modelling needs fewer parameters to describe the molecular electron density and can be more easily incorporated in molecular modelling software for the computation of electrostatic properties. The construction method of the database is described. In order to analyse to what extent this modelling method can be used to derive meaningful molecular properties, it has been applied to the urea molecule and to biotin/streptavidin, a protein/ligand complex.

Seasonal evolution of soil and plant parameters on the agricultural Gebesee test site: a database for the set-up and validation of EO-LDAS and satellite-aided retrieval models

NASA Astrophysics Data System (ADS)

Truckenbrodt, Sina C.; Schmullius, Christiane C.

2018-03-01

Ground reference data are a prerequisite for the calibration, update, and validation of retrieval models facilitating the monitoring of land parameters based on Earth Observation data. Here, we describe the acquisition of a comprehensive ground reference database which was created to test and validate the recently developed Earth Observation Land Data Assimilation System (EO-LDAS) and products derived from remote sensing observations in the visible and infrared range. In situ data were collected for seven crop types (winter barley, winter wheat, spring wheat, durum, winter rape, potato, and sugar beet) cultivated on the agricultural Gebesee test site, central Germany, in 2013 and 2014. The database contains information on hyperspectral surface reflectance factors, the evolution of biophysical and biochemical plant parameters, phenology, surface conditions, atmospheric states, and a set of ground control points. Ground reference data were gathered at an approximately weekly resolution and on different spatial scales to investigate variations within and between acreages. In situ data collected less than 1 day apart from satellite acquisitions (RapidEye, SPOT 5, Landsat-7 and -8) with a cloud coverage ≤ 25 % are available for 10 and 15 days in 2013 and 2014, respectively. The measurements show that the investigated growing seasons were characterized by distinct meteorological conditions causing interannual variations in the parameter evolution. Here, the experimental design of the field campaigns, and methods employed in the determination of all parameters, are described in detail. Insights into the database are provided and potential fields of application are discussed. The data will contribute to a further development of crop monitoring methods based on remote sensing techniques. The database is freely available at PANGAEA (https://doi.org/10.1594/PANGAEA.874251).

Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0.

PubMed

Wang, Shirley V; Schneeweiss, Sebastian; Berger, Marc L; Brown, Jeffrey; de Vries, Frank; Douglas, Ian; Gagne, Joshua J; Gini, Rosa; Klungel, Olaf; Mullins, C Daniel; Nguyen, Michael D; Rassen, Jeremy A; Smeeth, Liam; Sturkenboom, Miriam

2017-09-01

Defining a study population and creating an analytic dataset from longitudinal healthcare databases involves many decisions. Our objective was to catalogue scientific decisions underpinning study execution that should be reported to facilitate replication and enable assessment of validity of studies conducted in large healthcare databases. We reviewed key investigator decisions required to operate a sample of macros and software tools designed to create and analyze analytic cohorts from longitudinal streams of healthcare data. A panel of academic, regulatory, and industry experts in healthcare database analytics discussed and added to this list. Evidence generated from large healthcare encounter and reimbursement databases is increasingly being sought by decision-makers. Varied terminology is used around the world for the same concepts. Agreeing on terminology and which parameters from a large catalogue are the most essential to report for replicable research would improve transparency and facilitate assessment of validity. At a minimum, reporting for a database study should provide clarity regarding operational definitions for key temporal anchors and their relation to each other when creating the analytic dataset, accompanied by an attrition table and a design diagram. A substantial improvement in reproducibility, rigor and confidence in real world evidence generated from healthcare databases could be achieved with greater transparency about operational study parameters used to create analytic datasets from longitudinal healthcare databases. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Influence relevance voting: an accurate and interpretable virtual high throughput screening method.

PubMed

Swamidass, S Joshua; Azencott, Chloé-Agathe; Lin, Ting-Wan; Gramajo, Hugo; Tsai, Shiou-Chuan; Baldi, Pierre

2009-04-01

Given activity training data from high-throughput screening (HTS) experiments, virtual high-throughput screening (vHTS) methods aim to predict in silico the activity of untested chemicals. We present a novel method, the Influence Relevance Voter (IRV), specifically tailored for the vHTS task. The IRV is a low-parameter neural network which refines a k-nearest neighbor classifier by nonlinearly combining the influences of a chemical's neighbors in the training set. Influences are decomposed, also nonlinearly, into a relevance component and a vote component. The IRV is benchmarked using the data and rules of two large, open, competitions, and its performance compared to the performance of other participating methods, as well as of an in-house support vector machine (SVM) method. On these benchmark data sets, IRV achieves state-of-the-art results, comparable to the SVM in one case, and significantly better than the SVM in the other, retrieving three times as many actives in the top 1% of its prediction-sorted list. The IRV presents several other important advantages over SVMs and other methods: (1) the output predictions have a probabilistic semantic; (2) the underlying inferences are interpretable; (3) the training time is very short, on the order of minutes even for very large data sets; (4) the risk of overfitting is minimal, due to the small number of free parameters; and (5) additional information can easily be incorporated into the IRV architecture. Combined with its performance, these qualities make the IRV particularly well suited for vHTS.

Predicting missing links in complex networks based on common neighbors and distance

PubMed Central

Yang, Jinxuan; Zhang, Xiao-Dong

2016-01-01

The algorithms based on common neighbors metric to predict missing links in complex networks are very popular, but most of these algorithms do not account for missing links between nodes with no common neighbors. It is not accurate enough to reconstruct networks by using these methods in some cases especially when between nodes have less common neighbors. We proposed in this paper a new algorithm based on common neighbors and distance to improve accuracy of link prediction. Our proposed algorithm makes remarkable effect in predicting the missing links between nodes with no common neighbors and performs better than most existing currently used methods for a variety of real-world networks without increasing complexity. PMID:27905526

Merging a Terrain-Based Parameter and Snow Particle Counter Data for the Assessment of Snow Redistribution in the Col du Lac Blanc Area

NASA Astrophysics Data System (ADS)

Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Vionnet, Vincent; Guyomarc'h, Gilbert; Heiser, Micha; Nishimura, Kouichi

2015-04-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns. It does not, however, provide a quantitative estimate of changes in snow depths. The objective of our research was to introduce a new parameter to quantify changes in snow depths in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its consistently bi-modal wind directions. Our work focused on two pronounced, approximately 10 m high terrain breaks, and we worked with 1 m resolution digital snow surface models (DSM). The DSM and measured changes in snow depths were obtained with high-accuracy terrestrial laser scan (TLS) measurements. First we calculated the terrain-based parameter Sx on a digital snow surface model and correlated Sx with measured changes in snow-depths (Δ SH). Results showed that Δ SH can be approximated by Δ SHestimated = α * Sx, where α is a newly introduced parameter. The parameter α has shown to be linked to the amount of snow deposited influenced by blowing snow flux. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter α . To simulate the development of the snow surface in dependency of Sx, SPC flux and time, we apply a simple cellular automata system. The system consists of raster cells that develop through discrete time steps according to a set of rules. The rules are based on the states of neighboring cells. Our model assumes snow transport in dependency of Sx gradients between neighboring cells. The cells evolve based on difference quotients between neighbouring cells. Our analyses and results are steps towards using the terrain-based parameter Sx, coupled with SPC data, to quantitatively estimate changes in snow depths, using high raster resolutions of 1 m.

[Design of computerised database for clinical and basic management of uveal melanoma].

PubMed

Bande Rodríguez, M F; Santiago Varela, M; Blanco Teijeiro, M J; Mera Yañez, P; Pardo Perez, M; Capeans Tome, C; Piñeiro Ces, A

2012-09-01

The uveal melanoma is the most common primary intraocular tumour in adults. The objective of this work is to show how a computerised database has been formed with specific applications, for clinical and research use, to an extensive group of patients diagnosed with uveal melanoma. For the design of the database a selection of categories, attributes and values was created based on the classifications and parameters given by various authors of articles which have had great relevance in the field of uveal melanoma in recent years. The database has over 250 patient entries with specific information on their clinical history, diagnosis, treatment and progress. It enables us to search any parameter of the entry and make quick and simple statistical studies of them. The database models have been transformed into a basic tool for clinical practice, as they are an efficient way of storing, compiling and selective searching of information. When creating a database it is very important to define a common strategy and the use of a standard language. Copyright © 2011 Sociedad Española de Oftalmología. Published by Elsevier Espana. All rights reserved.

Comparative Evaluation of Registration Algorithms in Different Brain Databases With Varying Difficulty: Results and Insights

PubMed Central

Akbari, Hamed; Bilello, Michel; Da, Xiao; Davatzikos, Christos

2015-01-01

Evaluating various algorithms for the inter-subject registration of brain magnetic resonance images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated image registration algorithms in specific tasks or using specific databases (e.g., only for skull-stripped images, only for single-site images, etc.). Consequently, the choice of registration algorithms seems task- and usage/parameter-dependent. Nevertheless, recent large-scale, often multi-institutional imaging-related studies create the need and raise the question whether some registration algorithms can 1) generally apply to various tasks/databases posing various challenges; 2) perform consistently well, and while doing so, 3) require minimal or ideally no parameter tuning. In seeking answers to this question, we evaluated 12 general-purpose registration algorithms, for their generality, accuracy and robustness. We fixed their parameters at values suggested by algorithm developers as reported in the literature. We tested them in 7 databases/tasks, which present one or more of 4 commonly-encountered challenges: 1) inter-subject anatomical variability in skull-stripped images; 2) intensity homogeneity, noise and large structural differences in raw images; 3) imaging protocol and field-of-view (FOV) differences in multi-site data; and 4) missing correspondences in pathology-bearing images. Totally 7,562 registrations were performed. Registration accuracies were measured by (multi-)expert-annotated landmarks or regions of interest (ROIs). To ensure reproducibility, we used public software tools, public databases (whenever possible), and we fully disclose the parameter settings. We show evaluation results, and discuss the performances in light of algorithms’ similarity metrics, transformation models and optimization strategies. We also discuss future directions for the algorithm development and evaluations. PMID:24951685

Speed-dependent Voigt lineshape parameter database from dual frequency comb measurements up to 1305 K. Part I: Pure H2O absorption, 6801-7188 cm-1

NASA Astrophysics Data System (ADS)

Schroeder, Paul J.; Cich, Matthew J.; Yang, Jinyu; Giorgetta, Fabrizio R.; Swann, William C.; Coddington, Ian; Newbury, Nathan R.; Drouin, Brian J.; Rieker, Gregory B.

2018-05-01

We measure speed-dependent Voigt lineshape parameters with temperature-dependence exponents for several hundred spectroscopic features of pure water spanning 6801-7188 cm-1. The parameters are extracted from broad bandwidth, high-resolution dual frequency comb absorption spectra with multispectrum fitting techniques. The data encompass 25 spectra ranging from 296 K to 1305 K and 1 to 17 Torr of pure water vapor. We present the extracted parameters, compare them to published data, and present speed-dependence, self-shift, and self-broadening temperature-dependent parameters for the first time. Lineshape data is extracted using a quadratic speed-dependent Voigt profile and a single self-broadening power law temperature-dependence exponent over the entire temperature range. The results represent an important step toward a new high-temperature database using advanced lineshape profiles.

Panel data models with spatial correlation: Estimation theory and an empirical investigation of the United States wholesale gasoline industry

NASA Astrophysics Data System (ADS)

Kapoor, Mudit

The first part of my dissertation considers the estimation of a panel data model with error components that are both spatially and time-wise correlated. The dissertation combines widely used model for spatial correlation (Cliff and Ord (1973, 1981)) with the classical error component panel data model. I introduce generalizations of the generalized moments (GM) procedure suggested in Kelejian and Prucha (1999) for estimating the spatial autoregressive parameter in case of a single cross section. I then use those estimators to define feasible generalized least squares (GLS) procedures for the regression parameters. I give formal large sample results concerning the consistency of the proposed GM procedures, as well as the consistency and asymptotic normality of the proposed feasible GLS procedures. The new estimators remain computationally feasible even in large samples. The second part of my dissertation employs a Cliff-Ord-type model to empirically estimate the nature and extent of price competition in the US wholesale gasoline industry. I use data on average weekly wholesale gasoline price for 289 terminals (distribution facilities) in the US. Data on demand factors, cost factors and market structure that affect price are also used. I consider two time periods, a high demand period (August 1999) and a low demand period (January 2000). I find a high level of competition in prices between neighboring terminals. In particular, price in one terminal is significantly and positively correlated to the price of its neighboring terminal. Moreover, I find this to be much higher during the low demand period, as compared to the high demand period. In contrast to previous work, I include for each terminal the characteristics of the marginal customer by controlling for demand factors in the neighboring location. I find these demand factors to be important during period of high demand and insignificant during the low demand period. Furthermore, I have also considered spatial correlation in unobserved factors that affect price. I find it to be high and significant only during the low demand period. Not correcting for it leads to incorrect inferences regarding exogenous explanatory variables.

Variable-length analog of Stavskaya process: A new example of misleading simulation

NASA Astrophysics Data System (ADS)

Ramos, A. D.; Silva, F. S. G.; Sousa, C. S.; Toom, A.

2017-05-01

This article presents a new example intended to showcase limitations of computer simulations in the study of random processes with local interaction. For this purpose, we examine a new version of the well-known Stavskaya process, which is a discrete-time analog of the well-known contact processes. Like the bulk of random processes studied till now, the Stavskaya process is constant-length, that is, its components do not appear or disappear in the course of its functioning. The process, which we study here and call Variable Stavskaya, VS, is similar to Stavskaya; it is discrete-time; its states are bi-infinite sequences, whose terms take only two values (denoted here as "minus" and "plus"), and the measure concentrated in the configuration "all pluses" is invariant. However, it is a variable length, which means that its components, also called particles, may appear and disappear under its action. The operator VS is a composition of the following two operators. The first operator, called "birth," depends on a real parameter β; it creates a new component in the state "plus" between every two neighboring components with probability β independently from what happens at other places. The second operator, called "murder," depends on a real parameter α and acts in the following way: whenever a plus is a left neighbor of a minus, this plus disappears (as if murdered by that minus which is its right neighbor) with probability α independently from what happens to other particles. We prove for any α <1 and any β >0 and any initial measure μ that the sequence μ (𝖵𝖲)t (the result of t iterative applications of VS to μ) tends to the measure δ⊕ (concentrated in "all pluses") as t →∞ . Such a behavior is often called ergodic. However, the Monte Carlo simulations and mean-field approximations, which we performed, behaved as if μ (𝖵𝖲)t tended to δ⊕ much slower for some α ,β ,μ than for some others. Based on these numerical results, we conjecture that 𝖵𝖲 has phases, but not in that simple sense as the classical Stavskaya process.

Identifying influential neighbors in animal flocking

PubMed Central

Jiang, Li; Giuggioli, Luca; Escobedo, Ramón; Sire, Clément; Han, Zhangang

2017-01-01

Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors. PMID:29161269

A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

NASA Astrophysics Data System (ADS)

Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

2017-12-01

Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer than surface) signature over fresh snow cover.

The MAO NASU Plate Archive Database. Current Status and Perspectives

NASA Astrophysics Data System (ADS)

Pakuliak, L. K.; Sergeeva, T. P.

2006-04-01

The preliminary online version of the database of the MAO NASU plate archive is constructed on the basis of the relational database management system MySQL and permits an easy supplement of database with new collections of astronegatives, provides a high flexibility in constructing SQL-queries for data search optimization, PHP Basic Authorization protected access to administrative interface and wide range of search parameters. The current status of the database will be reported and the brief description of the search engine and means of the database integrity support will be given. Methods and means of the data verification and tasks for the further development will be discussed.

Distribution and Diversity of Microbial Eukaryotes in Bathypelagic Waters of the South China Sea.

PubMed

Xu, Dapeng; Jiao, Nianzhi; Ren, Rui; Warren, Alan

2017-05-01

Little is known about the biodiversity of microbial eukaryotes in the South China Sea, especially in waters at bathyal depths. Here, we employed SSU rDNA gene sequencing to reveal the diversity and community structure across depth and distance gradients in the South China Sea. Vertically, the highest alpha diversity was found at 75-m depth. The communities of microbial eukaryotes were clustered into shallow-, middle-, and deep-water groups according to the depth from which they were collected, indicating a depth-related diversity and distribution pattern. Rhizaria sequences dominated the microeukaryote community and occurred in all samples except those from less than 50-m deep, being most abundant near the sea floor where they contributed ca. 64-97% and 40-74% of the total sequences and OTUs recovered, respectively. A large portion of rhizarian OTUs has neither a nearest named neighbor nor a nearest neighbor in the GenBank database which indicated the presence of new phylotypes in the South China Sea. Given their overwhelming abundance and richness, further phylogenetic analysis of rhizarians were performed and three new genetic clusters were revealed containing sequences retrieved from the deep waters of the South China Sea. Our results shed light on the diversity and community structure of microbial eukaryotes in this not yet fully explored area. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Competition Among Reputations in the 2D Sznajd Model: Spontaneous Emergence of Democratic States

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Forgerini, Fabricio L.

2012-04-01

We propose a modification in the Sznajd sociophysics model defined on the square lattice. For this purpose, we consider reputation—a mechanism limiting the agents' persuasive power. The reputation is introduced as a time-dependent score, which can be positive or negative. This mechanism avoids dictatorship (full consensus, all spins parallel) for a wide range of model parameters. We consider two different situations: case 1, in which the agents' reputation increases for each persuaded neighbor, and case 2, in which the agents' reputation increases for each persuasion and decreases when a neighbor keeps his opinion. Our results show that the introduction of reputation avoids full consensus even for initial densities of up spins greater than 1/2. The relaxation times follow a log-normal-like distribution in both cases, but they are larger in case 2 due to the competition among reputations. In addition, we show that the usual phase transition occurs and depends on the initial concentration d of individuals with the same opinion, but the critical points d c in the two cases are different.

Orthogonal Polynomials on the Unit Circle with Fibonacci Verblunsky Coefficients, II. Applications

NASA Astrophysics Data System (ADS)

Damanik, David; Munger, Paul; Yessen, William N.

2013-10-01

We consider CMV matrices with Verblunsky coefficients determined in an appropriate way by the Fibonacci sequence and present two applications of the spectral theory of such matrices to problems in mathematical physics. In our first application we estimate the spreading rates of quantum walks on the line with time-independent coins following the Fibonacci sequence. The estimates we obtain are explicit in terms of the parameters of the system. In our second application, we establish a connection between the classical nearest neighbor Ising model on the one-dimensional lattice in the complex magnetic field regime, and CMV operators. In particular, given a sequence of nearest-neighbor interaction couplings, we construct a sequence of Verblunsky coefficients, such that the support of the Lee-Yang zeros of the partition function for the Ising model in the thermodynamic limit coincides with the essential spectrum of the CMV matrix with the constructed Verblunsky coefficients. Under certain technical conditions, we also show that the zeros distribution measure coincides with the density of states measure for the CMV matrix.

Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freitas, Celso, E-mail: cbnfreitas@gmail.com; Macau, Elbert, E-mail: elbert.macau@inpe.br; Pikovsky, Arkady, E-mail: pikovsky@uni-potsdam.de

2015-04-15

We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the fullmore » synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.« less

Tuning of quantum entanglement in molecular quantum cellular automata based on mixed-valence tetrameric units.

PubMed

Palii, Andrew; Tsukerblat, Boris

2016-10-25

In this article we consider two coupled tetrameric mixed-valence (MV) units accommodating electron pairs, which play the role of cells in molecular quantum cellular automata. It is supposed that the Coulombic interaction between instantly localized electrons within the cell markedly inhibits the transfer processes between the redox centers. Under this condition, as well as due to the vibronic localization of the electron pair, the cell can encode binary information, which is controlled by neighboring cells. We show that under certain conditions the two low-lying vibronic spin levels of the cell (ground and first excited states) can be regarded as originating from an effective spin-spin interaction. This is shown to depend on the internal parameters of the cell as well as on the induced polarization. Within this simplified two-level picture we evaluate the quantum entanglement in the system represented by the two electrons in the cell and show how the entanglement within the cell and concurrence can be controlled via polarization of the neighboring cells and temperature.

Crystal induced phosphorescence from Benz(a)anthracene microcrystals at room temperature

NASA Astrophysics Data System (ADS)

Maity, Samir; Mazumdar, Prativa; Shyamal, Milan; Sahoo, Gobinda Prasad; Misra, Ajay

2016-03-01

Pure organic compounds that are also phosphorescent at room temperature are very rare in literature. Here, we report efficient phosphorescence emission from aggregated hydrosol of Benz(a)anthracene (BaA) at room temperature. Aggregated hydrosol of BaA has been synthesized by re-precipitation method and SDS is used as morphology directing agent. Morphology of the particles is characterized using optical and scanning electronic microcopy (SEM). Photophysical properties of the aggregated hydrosol are carried out using UV-vis, steady state and time resolved fluorescence study. The large stoke shifted structured emission from aggregated hydrosol of BaA has been explained due to phosphorescence emission of BaA at room temperature. In the crystalline state, the restricted intermolecular motions (RIM) such as rotations and vibrations are activated by crystal lattice. This rigidification effect makes the chromophore phosphorescent at room temperature. The possible stacking arrangement of the neighboring BaA within the aggregates has been substantiated by computing second order Fukui parameter as local reactivity descriptors. Computational study also reveals that the neighboring BaA molecules are present in parallel slipped conformation in its aggregated crystalline form.

An asymmetric mesoscopic model for single bulges in RNA

NASA Astrophysics Data System (ADS)

de Oliveira Martins, Erik; Weber, Gerald

2017-10-01

Simple one-dimensional DNA or RNA mesoscopic models are of interest for their computational efficiency while retaining the key elements of the molecular interactions. However, they only deal with perfectly formed DNA or RNA double helices and consider the intra-strand interactions to be the same on both strands. This makes it difficult to describe highly asymmetric structures such as bulges and loops and, for instance, prevents the application of mesoscopic models to determine RNA secondary structures. Here we derived the conditions for the Peyrard-Bishop mesoscopic model to overcome these limitations and applied it to the calculation of single bulges, the smallest and simplest of these asymmetric structures. We found that these theoretical conditions can indeed be applied to any situation where stacking asymmetry needs to be considered. The full set of parameters for group I RNA bulges was determined from experimental melting temperatures using an optimization procedure, and we also calculated average opening profiles for several RNA sequences. We found that guanosine bulges show the strongest perturbation on their neighboring base pairs, considerably reducing the on-site interactions of their neighboring base pairs.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Dynamic Evolution with Limited Learning Information on a Small-World Network

NASA Astrophysics Data System (ADS)

Dong, Lin-Rong

2010-09-01

This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition.

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

NASA Technical Reports Server (NTRS)

Saeed, M.; Lieu, C.; Raber, G.; Mark, R. G.

2002-01-01

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

Web based tools for data manipulation, visualisation and validation with interactive georeferenced graphs

NASA Astrophysics Data System (ADS)

Ivankovic, D.; Dadic, V.

2009-04-01

Some of oceanographic parameters have to be manually inserted into database; some (for example data from CTD probe) are inserted from various files. All this parameters requires visualization, validation and manipulation from research vessel or scientific institution, and also public presentation. For these purposes is developed web based system, containing dynamic sql procedures and java applets. Technology background is Oracle 10g relational database, and Oracle application server. Web interfaces are developed using PL/SQL stored database procedures (mod PL/SQL). Additional parts for data visualization include use of Java applets and JavaScript. Mapping tool is Google maps API (javascript) and as alternative java applet. Graph is realized as dynamically generated web page containing java applet. Mapping tool and graph are georeferenced. That means that click on some part of graph, automatically initiate zoom or marker onto location where parameter was measured. This feature is very useful for data validation. Code for data manipulation and visualization are partially realized with dynamic SQL and that allow as to separate data definition and code for data manipulation. Adding new parameter in system requires only data definition and description without programming interface for this kind of data.

Studies of the DIII-D disruption database using Machine Learning algorithms

NASA Astrophysics Data System (ADS)

Rea, Cristina; Granetz, Robert; Meneghini, Orso

2017-10-01

A Random Forests Machine Learning algorithm, trained on a large database of both disruptive and non-disruptive DIII-D discharges, predicts disruptive behavior in DIII-D with about 90% of accuracy. Several algorithms have been tested and Random Forests was found superior in performances for this particular task. Over 40 plasma parameters are included in the database, with data for each of the parameters taken from 500k time slices. We focused on a subset of non-dimensional plasma parameters, deemed to be good predictors based on physics considerations. Both binary (disruptive/non-disruptive) and multi-label (label based on the elapsed time before disruption) classification problems are investigated. The Random Forests algorithm provides insight on the available dataset by ranking the relative importance of the input features. It is found that q95 and Greenwald density fraction (n/nG) are the most relevant parameters for discriminating between DIII-D disruptive and non-disruptive discharges. A comparison with the Gradient Boosted Trees algorithm is shown and the first results coming from the application of regression algorithms are presented. Work supported by the US Department of Energy under DE-FC02-04ER54698, DE-SC0014264 and DE-FG02-95ER54309.

A technique for routinely updating the ITU-R database using radio occultation electron density profiles

NASA Astrophysics Data System (ADS)

Brunini, Claudio; Azpilicueta, Francisco; Nava, Bruno

2013-09-01

Well credited and widely used ionospheric models, such as the International Reference Ionosphere or NeQuick, describe the variation of the electron density with height by means of a piecewise profile tied to the F2-peak parameters: the electron density,, and the height, . Accurate values of these parameters are crucial for retrieving reliable electron density estimations from those models. When direct measurements of these parameters are not available, the models compute the parameters using the so-called ITU-R database, which was established in the early 1960s. This paper presents a technique aimed at routinely updating the ITU-R database using radio occultation electron density profiles derived from GPS measurements gathered from low Earth orbit satellites. Before being used, these radio occultation profiles are validated by fitting to them an electron density model. A re-weighted Least Squares algorithm is used for down-weighting unreliable measurements (occasionally, entire profiles) and to retrieve and values—together with their error estimates—from the profiles. These values are used to monthly update the database, which consists of two sets of ITU-R-like coefficients that could easily be implemented in the IRI or NeQuick models. The technique was tested with radio occultation electron density profiles that are delivered to the community by the COSMIC/FORMOSAT-3 mission team. Tests were performed for solstices and equinoxes seasons in high and low-solar activity conditions. The global mean error of the resulting maps—estimated by the Least Squares technique—is between and elec/m for the F2-peak electron density (which is equivalent to 7 % of the value of the estimated parameter) and from 2.0 to 5.6 km for the height (2 %).

Frog sound identification using extended k-nearest neighbor classifier

NASA Astrophysics Data System (ADS)

Mukahar, Nordiana; Affendi Rosdi, Bakhtiar; Athiar Ramli, Dzati; Jaafar, Haryati

2017-09-01

Frog sound identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed to evaluate the accuracy of frog sound identification. This paper presents a frog sound identification with Extended k-Nearest Neighbor (EKNN) classifier. The EKNN classifier integrates the nearest neighbors and mutual sharing of neighborhood concepts, with the aims of improving the classification performance. It makes a prediction based on who are the nearest neighbors of the testing sample and who consider the testing sample as their nearest neighbors. In order to evaluate the classification performance in frog sound identification, the EKNN classifier is compared with competing classifier, k -Nearest Neighbor (KNN), Fuzzy k -Nearest Neighbor (FKNN) k - General Nearest Neighbor (KGNN)and Mutual k -Nearest Neighbor (MKNN) on the recorded sounds of 15 frog species obtained in Malaysia forest. The recorded sounds have been segmented using Short Time Energy and Short Time Average Zero Crossing Rate (STE+STAZCR), sinusoidal modeling (SM), manual and the combination of Energy (E) and Zero Crossing Rate (ZCR) (E+ZCR) while the features are extracted by Mel Frequency Cepstrum Coefficient (MFCC). The experimental results have shown that the EKNCN classifier exhibits the best performance in terms of accuracy compared to the competing classifiers, KNN, FKNN, GKNN and MKNN for all cases.

Sound propagation and absorption in foam - A distributed parameter model.

NASA Technical Reports Server (NTRS)

Manson, L.; Lieberman, S.

1971-01-01

Liquid-base foams are highly effective sound absorbers. A better understanding of the mechanisms of sound absorption in foams was sought by exploration of a mathematical model of bubble pulsation and coupling and the development of a distributed-parameter mechanical analog. A solution by electric-circuit analogy was thus obtained and transmission-line theory was used to relate the physical properties of the foams to the characteristic impedance and propagation constants of the analog transmission line. Comparison of measured physical properties of the foam with values obtained from measured acoustic impedance and propagation constants and the transmission-line theory showed good agreement. We may therefore conclude that the sound propagation and absorption mechanisms in foam are accurately described by the resonant response of individual bubbles coupled to neighboring bubbles.

Adaptive local linear regression with application to printer color management.

PubMed

Gupta, Maya R; Garcia, Eric K; Chin, Erika

2008-06-01

Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

Social dilemmas in multistrategy evolutionary potential games

NASA Astrophysics Data System (ADS)

Szabó, György; Bunth, Gergely

2018-01-01

The nature of social dilemmas is studied in n -strategy evolutionary potential games on a square lattice with nearest-neighbor interactions and the logit rule. For symmetric games with symmetric payoff matrices there are no dilemmas because of the coincidence of individual and common interests. The dilemmas are caused by the antisymmetric parts of the self- and cross-dependent payoff components if it modifies the preferred Nash equilibrium. The contentment of players and the emergence of dilemmas in the preferred Nash equilibria are illustrated on some two-dimensional cross sections of the parameter space.

Condensation in AN Economic Model with Brand Competition

NASA Astrophysics Data System (ADS)

Casillas, L.; Espinosa, F. J.; Huerta-Quintanilla, R.; Rodriguez-Achach, M.

We present a linear agent based model on brand competition. Each agent belongs to one of the two brands and interacts with its nearest neighbors. In the process the agent can decide to change to the other brand if the move is beneficial. The numerical simulations show that the systems always condenses into a state when all agents belong to a single brand. We study the condensation times for different parameters of the model and the influence of different mechanisms to avoid condensation, like anti monopoly rules and brand fidelity.

Growth front nucleation of rubrene thin films for high mobility organic transistors

NASA Astrophysics Data System (ADS)

Hsu, C. H.; Deng, J.; Staddon, C. R.; Beton, P. H.

2007-11-01

We demonstrate a mode of thin film growth in which amorphous islands crystallize into highly oriented platelets. A cascade of crystallization is observed, in which platelets growing outward from a central nucleation point impinge on neighboring amorphous islands and provide a seed for further nucleation. Through control of growth parameters, it is possible to produce high quality thin films which are well suited to the formation of organic transistors. We demonstrate this through the fabrication of rubrene thin film transistors with high carrier mobility.

Transfer coefficients in ultracold strongly coupled plasma

NASA Astrophysics Data System (ADS)

Bobrov, A. A.; Vorob'ev, V. S.; Zelener, B. V.

2018-03-01

We use both analytical and molecular dynamic methods for electron transfer coefficients in an ultracold plasma when its temperature is small and the coupling parameter characterizing the interaction of electrons and ions exceeds unity. For these conditions, we use the approach of nearest neighbor to determine the average electron (ion) diffusion coefficient and to calculate other electron transfer coefficients (viscosity and electrical and thermal conductivities). Molecular dynamics simulations produce electronic and ionic diffusion coefficients, confirming the reliability of these results. The results compare favorably with experimental and numerical data from earlier studies.

Nitrogen-14 NQR Study of Energetic Materials

DTIC Science & Technology

1982-09-01

field at the nuclear site due to its neighbors. Results analogous to Equation 2.1.4-1 have also been derived and observed for a quadrupolar system...to a function of the type SAf/(A 2 + A2 such as Equation 2.1.1-2. Insufficient data have been taken so far to ascertain tie degree of agreemcnt with...average value, rather than HI, the peak value, is the important parameter and that there is good agreement of the data with the form of Equation 2.1.1-2

On aggregation in CA models in biology

NASA Astrophysics Data System (ADS)

Alber, Mark S.; Kiskowski, Audi

2001-12-01

Aggregation of randomly distributed particles into clusters of aligned particles is modeled using a cellular automata (CA) approach. The CA model accounts for interactions between more than one type of particle, in which pressures for angular alignment with neighbors compete with pressures for grouping by cell type. In the case of only one particle type clusters tend to unite into one big cluster. In the case of several types of particles the dynamics of clusters is more complicated and for specific choices of parameters particle sorting occurs simultaneously with the formation of clusters of aligned particles.

CRRES microelectronic test chip orbital data. II

NASA Technical Reports Server (NTRS)

Soli, G. A.; Blaes, B. R.; Buehler, M. G.; Ray, K.; Lin, Y.-S.

1992-01-01

Data from a MOSFET matrix on two JPL (CIT Jet Propulsion Laboratory) CRRES (Combined Release and Radiation Effects Satellite) chips, each behind different amounts of shielding, are presented. Space damage factors are nearly identical to ground test values for pMOSFETs. The results from neighboring rows of MOSFETs show similar radiation degradation. The SRD (Space Radiation Dosimeter) is used to measure the total dose accumulated by the JPL chips. A parameter extraction algorithm that does not underestimate threshold voltage shifts is used. Temperature effects are removed from the MOSFET data.

Concentrations of indoor pollutants database: User's manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-05-01

This manual describes the computer-based database on indoor air pollutants. This comprehensive database alloys helps utility personnel perform rapid searches on literature related to indoor air pollutants. Besides general information, it provides guidance for finding specific information on concentrations of indoor air pollutants. The manual includes information on installing and using the database as well as a tutorial to assist the user in becoming familiar with the procedures involved in doing bibliographic and summary section searches. The manual demonstrates how to search for information by going through a series of questions that provide search parameters such as pollutants type, year,more » building type, keywords (from a specific list), country, geographic region, author's last name, and title. As more and more parameters are specified, the list of references found in the data search becomes smaller and more specific to the user's needs. Appendixes list types of information that can be input into the database when making a request. The CIP database allows individual utilities to obtain information on indoor air quality based on building types and other factors in their own service territory. This information is useful for utilities with concerns about indoor air quality and the control of indoor air pollutants. The CIP database itself is distributed by the Electric Power Software Center and runs on IBM PC-compatible computers.« less

Concentrations of indoor pollutants database: User`s manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-05-01

This manual describes the computer-based database on indoor air pollutants. This comprehensive database alloys helps utility personnel perform rapid searches on literature related to indoor air pollutants. Besides general information, it provides guidance for finding specific information on concentrations of indoor air pollutants. The manual includes information on installing and using the database as well as a tutorial to assist the user in becoming familiar with the procedures involved in doing bibliographic and summary section searches. The manual demonstrates how to search for information by going through a series of questions that provide search parameters such as pollutants type, year,more » building type, keywords (from a specific list), country, geographic region, author`s last name, and title. As more and more parameters are specified, the list of references found in the data search becomes smaller and more specific to the user`s needs. Appendixes list types of information that can be input into the database when making a request. The CIP database allows individual utilities to obtain information on indoor air quality based on building types and other factors in their own service territory. This information is useful for utilities with concerns about indoor air quality and the control of indoor air pollutants. The CIP database itself is distributed by the Electric Power Software Center and runs on IBM PC-compatible computers.« less

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Aidan P.; Swiler, Laura P.; Trott, Christian R.

2015-03-15

Here, we present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1].more » The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.« less

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, A.P., E-mail: athomps@sandia.gov; Swiler, L.P., E-mail: lpswile@sandia.gov; Trott, C.R., E-mail: crtrott@sandia.gov

2015-03-15

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. Themore » SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.« less

Spin canting in a Dy-based single-chain magnet with dominant next-nearest-neighbor antiferromagnetic interactions

NASA Astrophysics Data System (ADS)

Bernot, K.; Luzon, J.; Caneschi, A.; Gatteschi, D.; Sessoli, R.; Bogani, L.; Vindigni, A.; Rettori, A.; Pini, M. G.

2009-04-01

We investigate theoretically and experimentally the static magnetic properties of single crystals of the molecular-based single-chain magnet of formula [Dy(hfac)3NIT(C6H4OPh)]∞ comprising alternating Dy3+ and organic radicals. The magnetic molar susceptibility χM displays a strong angular variation for sample rotations around two directions perpendicular to the chain axis. A peculiar inversion between maxima and minima in the angular dependence of χM occurs on increasing temperature. Using information regarding the monomeric building block as well as an ab initio estimation of the magnetic anisotropy of the Dy3+ ion, this “anisotropy-inversion” phenomenon can be assigned to weak one-dimensional ferromagnetism along the chain axis. This indicates that antiferromagnetic next-nearest-neighbor interactions between Dy3+ ions dominate, despite the large Dy-Dy separation, over the nearest-neighbor interactions between the radicals and the Dy3+ ions. Measurements of the field dependence of the magnetization, both along and perpendicularly to the chain, and of the angular dependence of χM in a strong magnetic field confirm such an interpretation. Transfer-matrix simulations of the experimental measurements are performed using a classical one-dimensional spin model with antiferromagnetic Heisenberg exchange interaction and noncollinear uniaxial single-ion anisotropies favoring a canted antiferromagnetic spin arrangement, with a net magnetic moment along the chain axis. The fine agreement obtained with experimental data provides estimates of the Hamiltonian parameters, essential for further study of the dynamics of rare-earth-based molecular chains.

Rapid production of optimal-quality reduced-resolution representations of very large databases

DOEpatents

Sigeti, David E.; Duchaineau, Mark; Miller, Mark C.; Wolinsky, Murray; Aldrich, Charles; Mineev-Weinstein, Mark B.

2001-01-01

View space representation data is produced in real time from a world space database representing terrain features. The world space database is first preprocessed. A database is formed having one element for each spatial region corresponding to a finest selected level of detail. A multiresolution database is then formed by merging elements and a strict error metric is computed for each element at each level of detail that is independent of parameters defining the view space. The multiresolution database and associated strict error metrics are then processed in real time for real time frame representations. View parameters for a view volume comprising a view location and field of view are selected. The error metric with the view parameters is converted to a view-dependent error metric. Elements with the coarsest resolution are chosen for an initial representation. Data set first elements from the initial representation data set are selected that are at least partially within the view volume. The first elements are placed in a split queue ordered by the value of the view-dependent error metric. If the number of first elements in the queue meets or exceeds a predetermined number of elements or whether the largest error metric is less than or equal to a selected upper error metric bound, the element at the head of the queue is force split and the resulting elements are inserted into the queue. Force splitting is continued until the determination is positive to form a first multiresolution set of elements. The first multiresolution set of elements is then outputted as reduced resolution view space data representing the terrain features.

Ecophysiological parameters for Pacific Northwest trees.

Treesearch

Amy E. Hessl; Cristina Milesi; Michael A. White; David L. Peterson; Robert E. Keane

2004-01-01

We developed a species- and location-specific database of published ecophysiological variables typically used as input parameters for biogeochemical models of coniferous and deciduous forested ecosystems in the Western United States. Parameters are based on the requirements of Biome-BGC, a widely used biogeochemical model that was originally parameterized for the...

Motion data classification on the basis of dynamic time warping with a cloud point distance measure

NASA Astrophysics Data System (ADS)

Switonski, Adam; Josinski, Henryk; Zghidi, Hafedh; Wojciechowski, Konrad

2016-06-01

The paper deals with the problem of classification of model free motion data. The nearest neighbors classifier which is based on comparison performed by Dynamic Time Warping transform with cloud point distance measure is proposed. The classification utilizes both specific gait features reflected by a movements of subsequent skeleton joints and anthropometric data. To validate proposed approach human gait identification challenge problem is taken into consideration. The motion capture database containing data of 30 different humans collected in Human Motion Laboratory of Polish-Japanese Academy of Information Technology is used. The achieved results are satisfactory, the obtained accuracy of human recognition exceeds 90%. What is more, the applied cloud point distance measure does not depend on calibration process of motion capture system which results in reliable validation.

The FP4026 Research Database on the fundamental period of RC infilled frame structures.

PubMed

Asteris, Panagiotis G

2016-12-01

The fundamental period of vibration appears to be one of the most critical parameters for the seismic design of buildings because it strongly affects the destructive impact of the seismic forces. In this article, important research data (entitled FP4026 Research Database (Fundamental Period-4026 cases of infilled frames) based on a detailed and in-depth analytical research on the fundamental period of reinforced concrete structures is presented. In particular, the values of the fundamental period which have been analytically determined are presented, taking into account the majority of the involved parameters. This database can be extremely valuable for the development of new code proposals for the estimation of the fundamental period of reinforced concrete structures fully or partially infilled with masonry walls.

Seeing is believing: on the use of image databases for visually exploring plant organelle dynamics.

PubMed

Mano, Shoji; Miwa, Tomoki; Nishikawa, Shuh-ichi; Mimura, Tetsuro; Nishimura, Mikio

2009-12-01

Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions.

PubMed

Sedykh, Alexander; Fourches, Denis; Duan, Jianmin; Hucke, Oliver; Garneau, Michel; Zhu, Hao; Bonneau, Pierre; Tropsha, Alexander

2013-04-01

Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

Marginal Fisher analysis and its variants for human gait recognition and content- based image retrieval.

PubMed

Xu, Dong; Yan, Shuicheng; Tao, Dacheng; Lin, Stephen; Zhang, Hong-Jiang

2007-11-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for human gait recognition and content-based image retrieval (CBIR). In this paper, we present extensions of our recently proposed marginal Fisher analysis (MFA) to address these problems. For human gait recognition, we first present a direct application of MFA, then inspired by recent advances in matrix and tensor-based dimensionality reduction algorithms, we present matrix-based MFA for directly handling 2-D input in the form of gray-level averaged images. For CBIR, we deal with the relevance feedback problem by extending MFA to marginal biased analysis, in which within-class compactness is characterized only by the distances between each positive sample and its neighboring positive samples. In addition, we present a new technique to acquire a direct optimal solution for MFA without resorting to objective function modification as done in many previous algorithms. We conduct comprehensive experiments on the USF HumanID gait database and the Corel image retrieval database. Experimental results demonstrate that MFA and its extensions outperform related algorithms in both applications.

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

Word naming times and psycholinguistic norms for Italian nouns.

PubMed

Barca, Laura; Burani, Cristina; Arduino, Lisa S

2002-08-01

The present study describes normative measures for 626 Italian simple nouns. The database (LEXVAR.XLS) is freely available for down-loading on the Web site http://wwwistc.ip.rm.cnr.it/materia/database/. For each of the 626 nouns, values for the following variables are reported: age of acquisition, familiarity, imageability, concreteness, adult written frequency, child written frequency, adult spoken frequency, number of orthographic neighbors, mean bigram frequency, length in syllables, and length in letters. A classification of lexical stress and of the type of word-initial phoneme is also provided. The intercorrelations among the variables, a factor analysis, and the effects of variables and of the extracted factors on word naming are reported. Naming latencies were affected primarily by a factor including word length and neighborhood size and by a word frequency factor. Neither a semantic factor including imageability, concreteness, and age of acquisition nor a factor defined by mean bigram frequency had significant effects on pronunciation times. These results hold for a language with shallow orthography, like Italian, for which lexical nonsemantic properties have been shown to affect reading aloud. These norms are useful in a variety of research areas involving the manipulation and control of stimulus attributes.

RASopathies: Presentation at the Genome, Interactome, and Phenome Levels.

PubMed

Pevec, Urska; Rozman, Neva; Gorsek, Blaz; Kunej, Tanja

2016-05-01

Clinical symptoms often reflect molecular correlations between mutated proteins. Alignment between interactome and phenome levels reveals new disease genes and connections between previously unrelated diseases. Despite a great potential for novel discoveries, this approach is still rarely used in genomics. In the present study, we analyzed the data of 6 syndromes belonging to the RASopathy class of disorders (RASopathies) and presented them as a model to study associations between genome, interactome, and phenome levels. Causative genes and clinical symptoms were collected from OMIM and NCBI GeneReviews databases for 6 syndromes: Noonan, Noonan syndrome with multiple lentigines, neurofibromatosis type 1, cardiofaciocutaneous, and Legius and Costello syndrome. The STRING tool was used for the identification of protein interactions. Six RASopathy syndromes were found to be associated with 12 causative genes. We constructed an interactome of RASopathy proteins and their neighbors and developed a database of 328 clinical symptoms. The collected data was presented at genome, interactome, and phenome levels and as an integrated network of all 3 data types. The present study provides a baseline for future studies of associations between interactome and phenome in RASopathies and could serve as a novel approach to analyze phenotypically and genetically related diseases.

Complex Consequences of Herbivory and Interplant Cues in Three Annual Plants

PubMed Central

Pearse, Ian S.; Porensky, Lauren M.; Yang, Louie H.; Stanton, Maureen L.; Karban, Richard; Bhattacharyya, Lisa; Cox, Rosa; Dove, Karin; Higgins, August; Kamoroff, Corrina; Kirk, Travis; Knight, Christopher; Koch, Rebecca; Parker, Corwin; Rollins, Hilary; Tanner, Kelsey

2012-01-01

Information exchange (or signaling) between plants following herbivore damage has recently been shown to affect plant responses to herbivory in relatively simple natural systems. In a large, manipulative field study using three annual plant species (Achyrachaena mollis, Lupinus nanus, and Sinapis arvensis), we tested whether experimental damage to a neighboring conspecific affected a plant's lifetime fitness and interactions with herbivores. By manipulating relatedness between plants, we assessed whether genetic relatedness of neighboring individuals influenced the outcome of having a damaged neighbor. Additionally, in laboratory feeding assays, we assessed whether damage to a neighboring plant specifically affected palatability to a generalist herbivore and, for S. arvensis, a specialist herbivore. Our study suggested a high level of contingency in the outcomes of plant signaling. For example, in the field, damaging a neighbor resulted in greater herbivory to A. mollis, but only when the damaged neighbor was a close relative. Similarly, in laboratory trials, the palatability of S. arvensis to a generalist herbivore increased after the plant was exposed to a damaged neighbor, while palatability to a specialist herbivore decreased. Across all species, damage to a neighbor resulted in decreased lifetime fitness, but only if neighbors were closely related. These results suggest that the outcomes of plant signaling within multi-species neighborhoods may be far more context-specific than has been previously shown. In particular, our study shows that herbivore interactions and signaling between plants are contingent on the genetic relationship between neighboring plants. Many factors affect the outcomes of plant signaling, and studies that clarify these factors will be necessary in order to assess the role of plant information exchange about herbivory in natural systems. PMID:22675439

Selenium hyperaccumulators facilitate selenium-tolerant neighbors via phytoenrichment and reduced herbivory.

PubMed

El Mehdawi, Ali F; Quinn, Colin F; Pilon-Smits, Elizabeth A H

2011-09-13

Soil surrounding selenium (Se) hyperaccumulator plants was shown earlier to be enriched in Se, impairing the growth of Se-sensitive plant species. Because Se levels in neighbors of hyperaccumulators were higher and Se has been shown to protect plants from herbivory, we investigate here the potential facilitating effect of Se hyperaccumulators on Se-tolerant neighboring species in the field. We measured growth and herbivory of Artemisia ludoviciana and Symphyotrichum ericoides as a function of their Se concentration and proximity to hyperaccumulators Astragalus bisulcatus and Stanleya pinnata. When growing next to hyperaccumulators, A. ludoviciana and S. ericoides contained 10- to 20-fold higher Se levels (800-2,000 mg kg(-1) DW) than when growing next to nonaccumulators. The roots of both species were predominantly (70%-90%) directed toward hyperaccumulator neighbors, not toward other neighbors. Moreover, neighbors of hyperaccumulators were 2-fold bigger, showed 2-fold less herbivory damage, and harbored 3- to 4-fold fewer arthropods. When used in laboratory choice and nonchoice grasshopper herbivory experiments, Se-rich neighbors of hyperaccumulators experienced less herbivory and caused higher grasshopper Se accumulation (10-fold) and mortality (4-fold). Enhanced soil Se levels around hyperaccumulators can facilitate growth of Se-tolerant plant species through reduced herbivory and enhanced growth. This study is the first to show facilitation via enrichment with a nonessential element. It is interesting that Se enrichment of hyperaccumulator neighbors may affect competition in two ways, by reducing growth of Se-sensitive neighbors while facilitating Se-tolerant neighbors. Via these competitive and facilitating effects, Se hyperaccumulators may affect plant community composition and, consequently, higher trophic levels. Copyright © 2011 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez del Rio, Manuel; Bianchi, Davide; Cocco, Daniele

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper,more » with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. Some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.« less

Detection of image structures using the Fisher information and the Rao metric.

PubMed

Maybank, Stephen J

2004-12-01

In many detection problems, the structures to be detected are parameterized by the points of a parameter space. If the conditional probability density function for the measurements is known, then detection can be achieved by sampling the parameter space at a finite number of points and checking each point to see if the corresponding structure is supported by the data. The number of samples and the distances between neighboring samples are calculated using the Rao metric on the parameter space. The Rao metric is obtained from the Fisher information which is, in turn, obtained from the conditional probability density function. An upper bound is obtained for the probability of a false detection. The calculations are simplified in the low noise case by making an asymptotic approximation to the Fisher information. An application to line detection is described. Expressions are obtained for the asymptotic approximation to the Fisher information, the volume of the parameter space, and the number of samples. The time complexity for line detection is estimated. An experimental comparison is made with a Hough transform-based method for detecting lines.

Hidden symmetries of the extended Kitaev-Heisenberg model: Implications for the honeycomb-lattice iridates A2IrO3

NASA Astrophysics Data System (ADS)

Chaloupka, Jiří; Khaliullin, Giniyat

2015-07-01

We have explored the hidden symmetries of a generic four-parameter nearest-neighbor spin model, allowed in honeycomb-lattice compounds under trigonal compression. Our method utilizes a systematic algorithm to identify all dual transformations of the model that map the Hamiltonian on itself, changing the parameters and providing exact links between different points in its parameter space. We have found the complete set of points of hidden SU(2) symmetry at which a seemingly highly anisotropic model can be mapped back on the Heisenberg model and inherits therefore its properties such as the presence of gapless Goldstone modes. The procedure used to search for the hidden symmetries is quite general and may be extended to other bond-anisotropic spin models and other lattices, such as the triangular, kagome, hyperhoneycomb, or harmonic-honeycomb lattices. We apply our findings to the honeycomb-lattice iridates Na2IrO3 and Li2IrO3 , and illustrate how they help to identify plausible values of the model parameters that are compatible with the available experimental data.

On the ab initio evaluation of Hubbard parameters. II. The κ-(BEDT-TTF)2Cu[N(CN)2]Br crystal

NASA Astrophysics Data System (ADS)

Fortunelli, Alessandro; Painelli, Anna

1997-05-01

A previously proposed approach for the ab initio evaluation of Hubbard parameters is applied to BEDT-TTF dimers. The dimers are positioned according to four geometries taken as the first neighbors from the experimental data on the κ-(BEDT-TTF)2Cu[N(CN)2]Br crystal. RHF-SCF, CAS-SCF and frozen-orbital calculations using the 6-31G** basis set are performed with different values of the total charge, allowing us to derive all the relevant parameters. It is found that the electronic structure of the BEDT-TTF planes is adequately described by the standard Extended Hubbard Model, with the off-diagonal electron-electron interaction terms (X and W) of negligible size. The derived parameters are in good agreement with available experimental data. Comparison with previous theoretical estimates shows that the t values compare well with those obtained from Extended Hückel Theory (whereas the minimal basis set estimates are completely unreliable). On the other hand, the Uaeff values exhibit an appreciable dependence on the chemical environment.

An embedded face-classification system for infrared images on an FPGA

NASA Astrophysics Data System (ADS)

Soto, Javier E.; Figueroa, Miguel

2014-10-01

We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

NASA Astrophysics Data System (ADS)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Confirmation of Two Sibling Species among Anopheles fluviatilis Mosquitoes in South and Southeastern Iran by Analysis of Cytochrome Oxidase I Gene.

PubMed

Naddaf, Saied Reza; Oshaghi, Mohammad Ali; Vatandoost, Hassan

2012-12-01

Anopheles fluviatilis, one of the major malaria vectors in Iran, is assumed to be a complex of sibling species. The aim of this study was to evaluate Cytochrome oxidase I (COI) gene alongside 28S-D3 as a diagnostic tool for identification of An. fluviatilis sibling species in Iran. DNA sample belonging to 24 An. fluviatilis mosquitoes from different geographical areas in south and southeastern Iran were used for amplification of COI gene followed by sequencing. The 474-475 bp COI sequences obtained in this study were aligned with 59 similar sequences of An. fluviatilis and a sequence of Anopheles minimus, as out group, from GenBank database. The distances between group and individual sequences were calculated and phylogenetic tree for obtained sequences was generated by using Kimura two parameter (K2P) model of neighbor-joining method. Phylogenetic analysis using COI gene grouped members of Fars Province (central Iran) in two distinct clades separate from other Iranian members representing Hormozgan, Kerman, and Sistan va Baluchestan Provinces. The mean distance between Iranian and Indian individuals was 1.66%, whereas the value between Fars Province individuals and the group comprising individuals from other areas of Iran was 2.06%. Presence of 2.06% mean distance between individuals from Fars Province and those from other areas of Iran is indicative of at least two sibling species in An. fluviatilis mosquitoes of Iran. This finding confirms earlier results based on RAPD-PCR and 28S-D3 analysis.

Rumor has it...: relay communication of stress cues in plants.

PubMed

Falik, Omer; Mordoch, Yonat; Quansah, Lydia; Fait, Aaron; Novoplansky, Ariel

2011-01-01

Recent evidence demonstrates that plants are able not only to perceive and adaptively respond to external information but also to anticipate forthcoming hazards and stresses. Here, we tested the hypothesis that unstressed plants are able to respond to stress cues emitted from their abiotically-stressed neighbors and in turn induce stress responses in additional unstressed plants located further away from the stressed plants. Pisum sativum plants were subjected to drought while neighboring rows of five unstressed plants on both sides, with which they could exchange different cue combinations. On one side, the stressed plant and its unstressed neighbors did not share their rooting volumes (UNSHARED) and thus were limited to shoot communication. On its other side, the stressed plant shared one of its rooting volumes with its nearest unstressed neighbor and all plants shared their rooting volumes with their immediate neighbors (SHARED), allowing both root and shoot communication. Fifteen minutes following drought induction, significant stomatal closure was observed in both the stressed plants and their nearest unstressed SHARED neighbors, and within one hour, all SHARED neighbors closed their stomata. Stomatal closure was not observed in the UNSHARED neighbors. The results demonstrate that unstressed plants are able to perceive and respond to stress cues emitted by the roots of their drought-stressed neighbors and, via 'relay cuing', elicit stress responses in further unstressed plants. Further work is underway to study the underlying mechanisms of this new mode of plant communication and its possible adaptive implications for the anticipation of forthcoming abiotic stresses by plants.

Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy.

PubMed

Dallmann, André; Ince, Ibrahim; Meyer, Michaela; Willmann, Stefan; Eissing, Thomas; Hempel, Georg

2017-11-01

In the past years, several repositories for anatomical and physiological parameters required for physiologically based pharmacokinetic modeling in pregnant women have been published. While providing a good basis, some important aspects can be further detailed. For example, they did not account for the variability associated with parameters or were lacking key parameters necessary for developing more detailed mechanistic pregnancy physiologically based pharmacokinetic models, such as the composition of pregnancy-specific tissues. The aim of this meta-analysis was to provide an updated and extended database of anatomical and physiological parameters in healthy pregnant women that also accounts for changes in the variability of a parameter throughout gestation and for the composition of pregnancy-specific tissues. A systematic literature search was carried out to collect study data on pregnancy-related changes of anatomical and physiological parameters. For each parameter, a set of mathematical functions was fitted to the data and to the standard deviation observed among the data. The best performing functions were selected based on numerical and visual diagnostics as well as based on physiological plausibility. The literature search yielded 473 studies, 302 of which met the criteria to be further analyzed and compiled in a database. In total, the database encompassed 7729 data. Although the availability of quantitative data for some parameters remained limited, mathematical functions could be generated for many important parameters. Gaps were filled based on qualitative knowledge and based on physiologically plausible assumptions. The presented results facilitate the integration of pregnancy-dependent changes in anatomy and physiology into mechanistic population physiologically based pharmacokinetic models. Such models can ultimately provide a valuable tool to investigate the pharmacokinetics during pregnancy in silico and support informed decision making regarding optimal dosing regimens in this vulnerable special population.

Private database queries based on counterfactual quantum key distribution

NASA Astrophysics Data System (ADS)

Zhang, Jia-Li; Guo, Fen-Zhuo; Gao, Fei; Liu, Bin; Wen, Qiao-Yan

2013-08-01

Based on the fundamental concept of quantum counterfactuality, we propose a protocol to achieve quantum private database queries, which is a theoretical study of how counterfactuality can be employed beyond counterfactual quantum key distribution (QKD). By adding crucial detecting apparatus to the device of QKD, the privacy of both the distrustful user and the database owner can be guaranteed. Furthermore, the proposed private-database-query protocol makes full use of the low efficiency in the counterfactual QKD, and by adjusting the relevant parameters, the protocol obtains excellent flexibility and extensibility.

Generative Models for Similarity-based Classification

DTIC Science & Technology

2007-01-01

NC), local nearest centroid (local NC), k-nearest neighbors ( kNN ), and condensed nearest neighbors (CNN) are all similarity-based classifiers which...vector machine to the k nearest neighbors of the test sample [80]. The SVM- KNN method was developed to address the robustness and dimensionality...concerns that afflict nearest neighbors and SVMs. Similarly to the nearest-means classifier, the SVM- KNN is a hybrid local and global classifier developed

The GTN-P Data Management System: A central database for permafrost monitoring parameters of the Global Terrestrial Network for Permafrost (GTN-P) and beyond

NASA Astrophysics Data System (ADS)

Lanckman, Jean-Pierre; Elger, Kirsten; Karlsson, Ævar Karl; Johannsson, Halldór; Lantuit, Hugues

2013-04-01

Permafrost is a direct indicator of climate change and has been identified as Essential Climate Variable (ECV) by the global observing community. The monitoring of permafrost temperatures, active-layer thicknesses and other parameters has been performed for several decades already, but it was brought together within the Global Terrestrial Network for Permafrost (GTN-P) in the 1990's only, including the development of measurement protocols to provide standardized data. GTN-P is the primary international observing network for permafrost sponsored by the Global Climate Observing System (GCOS) and the Global Terrestrial Observing System (GTOS), and managed by the International Permafrost Association (IPA). All GTN-P data was outfitted with an "open data policy" with free data access via the World Wide Web. The existing data, however, is far from being homogeneous: it is not yet optimized for databases, there is no framework for data reporting or archival and data documentation is incomplete. As a result, and despite the utmost relevance of permafrost in the Earth's climate system, the data has not been used by as many researchers as intended by the initiators of the programs. While the monitoring of many other ECVs has been tackled by organized international networks (e.g. FLUXNET), there is still no central database for all permafrost-related parameters. The European Union project PAGE21 created opportunities to develop this central database for permafrost monitoring parameters of GTN-P during the duration of the project and beyond. The database aims to be the one location where the researcher can find data, metadata, and information of all relevant parameters for a specific site. Each component of the Data Management System (DMS), including parameters, data levels and metadata formats were developed in cooperation with the GTN-P and the IPA. The general framework of the GTN-P DMS is based on an object oriented model (OOM), open for as many parameters as possible, and implemented into a spatial database. To ensure interoperability and enable potential inter-database search, field names are following international metadata standards and are based on a control vocabulary registry. Tools are developed to provide data processing, analysis capability, and quality control. Our system aims to be a reference model, improvable and reusable. It allows a maximum top-down and bottom-up data flow, giving scientists one global searchable data and metadata repository, the public a full access to scientific data, and the policy maker a powerful cartographic and statistical tool. To engage the international community in GTN-P, it was essential to develop an online interface for data upload. Aim for this was that it is easy-to-use and allows data input with a minimum of technical and personal effort. In addition to this, large efforts will have to be produced in order to be able to query, visualize and retrieve information over many platforms and type of measurements. Ultimately, it is not the layer in itself that matter, but more the relationship that these information layers maintain with each other.

Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

PubMed

Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel

2011-02-01

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Information mining in remote sensing imagery

NASA Astrophysics Data System (ADS)

Li, Jiang

The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and fuzzy normalized difference vegetation index (NDVI) pattern mining. The study results show the effectiveness of the proposed system prototype and the potentials for other applications in remote sensing.

Relationship between neighbor number and vibrational spectra in disordered colloidal clusters with attractive interactions

NASA Astrophysics Data System (ADS)

Yunker, Peter J.; Zhang, Zexin; Gratale, Matthew; Chen, Ke; Yodh, A. G.

2013-03-01

We study connections between vibrational spectra and average nearest neighbor number in disordered clusters of colloidal particles with attractive interactions. Measurements of displacement covariances between particles in each cluster permit calculation of the stiffness matrix, which contains effective spring constants linking pairs of particles. From the cluster stiffness matrix, we derive vibrational properties of corresponding "shadow" glassy clusters, with the same geometric configuration and interactions as the "source" cluster but without damping. Here, we investigate the stiffness matrix to elucidate the origin of the correlations between the median frequency of cluster vibrational modes and average number of nearest neighbors in the cluster. We find that the mean confining stiffness of particles in a cluster, i.e., the ensemble-averaged sum of nearest neighbor spring constants, correlates strongly with average nearest neighbor number, and even more strongly with median frequency. Further, we find that the average oscillation frequency of an individual particle is set by the total stiffness of its nearest neighbor bonds; this average frequency increases as the square root of the nearest neighbor bond stiffness, in a manner similar to the simple harmonic oscillator.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

Practice databases and their uses in clinical research.

PubMed

Tierney, W M; McDonald, C J

1991-04-01

A few large clinical information databases have been established within larger medical information systems. Although they are smaller than claims databases, these clinical databases offer several advantages: accurate and timely data, rich clinical detail, and continuous parameters (for example, vital signs and laboratory results). However, the nature of the data vary considerably, which affects the kinds of secondary analyses that can be performed. These databases have been used to investigate clinical epidemiology, risk assessment, post-marketing surveillance of drugs, practice variation, resource use, quality assurance, and decision analysis. In addition, practice databases can be used to identify subjects for prospective studies. Further methodologic developments are necessary to deal with the prevalent problems of missing data and various forms of bias if such databases are to grow and contribute valuable clinical information.

Dependence of growth of the phases of multiphase binary systems on the diffusion parameters

NASA Astrophysics Data System (ADS)

Molokhina, L. A.; Rogalin, V. E.; Filin, S. A.; Kaplunov, I. A.

2017-12-01

A mathematical model of the diffusion interaction of a binary system with several phases on the equilibrium phase diagram is presented. The theoretical and calculated dependences of the layer thickness of each phase in the multiphase diffusion zone on the isothermal annealing time and the ratio of the diffusion parameters in the neighboring phases with an unlimited supply of both components were constructed. The phase formation and growth in the diffusion zone during "reactive" diffusion corresponds to the equilibrium state diagram for two components, and the order of their appearance in the diffusion zone depends only on the ratio of the diffusion parameters in the phases themselves and on the duration of the incubation periods. The dependence of phase appearance on the incubation periods, annealing time, and difference in the movement rates of the components across the interface boundaries was obtained. An example of the application of the model for processing the experimental data on phase growth in a two-component three-phase system was given.

Spectroscopic signatures of different symmetries of the superconducting order parameter in metal-decorated graphene

NASA Astrophysics Data System (ADS)

Saari, Timo; Nieminen, Jouko; Bansil, Arun

2017-06-01

Motivated by the recent experiments indicating superconductivity in metal-decorated graphene sheets, we investigate their quasi-particle structure within the framework of an effective tight-binding Hamiltonian augmented by appropriate BCS-like pairing terms for p-type order parameter. The normal state band structure of graphene is modified not only through interaction with adsorbed metal atoms, but also due to the folding of bands at Brillouin zone boundaries resulting from a \\sqrt{3}× \\sqrt{3}R{{30}\\circ} reconstruction. Several different types of pairing symmetries are analyzed utilizing Nambu-Gorkov Green’s function techniques to show that p+\\text{i}p -symmetric nearest-neighbor pairing yields the most enhanced superconducting gap. The character of the order parameter depends on the nature of the atomic orbitals involved in the pairing process and exhibits interesting angular and radial asymmetries. Finally, we suggest a method to distinguish between singlet and triplet type superconductivity in the presence of magnetic substitutional impurities using scanning tunneling spectroscopy.

Tchebichef moment based restoration of Gaussian blurred images.

PubMed

Kumar, Ahlad; Paramesran, Raveendran; Lim, Chern-Loon; Dass, Sarat C

2016-11-10

With the knowledge of how edges vary in the presence of a Gaussian blur, a method that uses low-order Tchebichef moments is proposed to estimate the blur parameters: sigma (σ) and size (w). The difference between the Tchebichef moments of the original and the reblurred images is used as feature vectors to train an extreme learning machine for estimating the blur parameters (σ,w). The effectiveness of the proposed method to estimate the blur parameters is examined using cross-database validation. The estimated blur parameters from the proposed method are used in the split Bregman-based image restoration algorithm. A comparative analysis of the proposed method with three existing methods using all the images from the LIVE database is carried out. The results show that the proposed method in most of the cases performs better than the three existing methods in terms of the visual quality evaluated using the structural similarity index.

Magnetic compensation and critical properties of a mixed spin-(2, 3/2) Heisenberg single-walled nanotube superlattice

NASA Astrophysics Data System (ADS)

Mi, Bin-Zhou; Feng, Cui-Ju; Luo, Jian-Guo; Hu, De-Zhi

2018-01-01

In recent years, some theoretical interests have been focused on the binary alloy nanotubes and nanowires with mixed spins. Compared with ferrimagnetic nanowires, few studies have been done on ferrimagnetic nanotubes. In this paper, the magnetic properties of a mixed spin-(2, 3/2) Heisenberg single-walled nanotube superlattice are calculated by use of the double-time Green's function method within the random phase approximation and the Anderson and Callen's decoupling. Magnetic compensation and critical properties are obtained for a wide range of parameters in the Hamiltonian, and magnetic phase diagrams are plotted in the related planes. For Heisenberg single-walled nanotube superlattice model with Néel-type magnetic structure, anisotropy must be taken into account, and the easy-axis single-ion anisotropy is considered in this paper. The next nearest neighbor exchange interactions Jbb and/or single-ion anisotropy strength Db of the smaller spin sublattice were necessary in order to obtain a compensation point. The influence of the wall diameter number of the tubes, m, an important parameter of the system, on the compensation behavior is considered. Calculation shows that as Jbb and Db are fixed, only when m is beyond a certain minimum value, mmin, can compensation temperature Tcom appears, where the next nearest neighbor exchange interactions Jaa and single-ion anisotropy strength Da of the larger spin sublattice are absent. The compensation temperature and critical temperature increase with m rising, which indicates that the longitudinal correlation effect is enhanced and the fluctuation effect is weakened with the increase of m.

Modeling the frequency-dependent detective quantum efficiency of photon-counting x-ray detectors.

PubMed

Stierstorfer, Karl

2018-01-01

To find a simple model for the frequency-dependent detective quantum efficiency (DQE) of photon-counting detectors in the low flux limit. Formula for the spatial cross-talk, the noise power spectrum and the DQE of a photon-counting detector working at a given threshold are derived. Parameters are probabilities for types of events like single counts in the central pixel, double counts in the central pixel and a neighboring pixel or single count in a neighboring pixel only. These probabilities can be derived in a simple model by extensive use of Monte Carlo techniques: The Monte Carlo x-ray propagation program MOCASSIM is used to simulate the energy deposition from the x-rays in the detector material. A simple charge cloud model using Gaussian clouds of fixed width is used for the propagation of the electric charge generated by the primary interactions. Both stages are combined in a Monte Carlo simulation randomizing the location of impact which finally produces the required probabilities. The parameters of the charge cloud model are fitted to the spectral response to a polychromatic spectrum measured with our prototype detector. Based on the Monte Carlo model, the DQE of photon-counting detectors as a function of spatial frequency is calculated for various pixel sizes, photon energies, and thresholds. The frequency-dependent DQE of a photon-counting detector in the low flux limit can be described with an equation containing only a small set of probabilities as input. Estimates for the probabilities can be derived from a simple model of the detector physics. © 2017 American Association of Physicists in Medicine.

Ground-state phases of the spin-1 J1-J2 Heisenberg antiferromagnet on the honeycomb lattice

NASA Astrophysics Data System (ADS)

Li, P. H. Y.; Bishop, R. F.

2016-06-01

We study the zero-temperature quantum phase diagram of a spin-1 Heisenberg antiferromagnet on the honeycomb lattice with both nearest-neighbor exchange coupling J1>0 and frustrating next-nearest-neighbor coupling J2≡κ J1>0 , using the coupled cluster method implemented to high orders of approximation, and based on model states with different forms of classical magnetic order. For each we calculate directly in the bulk thermodynamic limit both ground-state low-energy parameters (including the energy per spin, magnetic order parameter, spin stiffness coefficient, and zero-field uniform transverse magnetic susceptibility) and their generalized susceptibilities to various forms of valence-bond crystalline (VBC) order, as well as the energy gap to the lowest-lying spin-triplet excitation. In the range 0 <κ <1 we find evidence for four distinct phases. Two of these are quasiclassical phases with antiferromagnetic long-range order, one with two-sublattice Néel order for κ <κc1=0.250(5 ) , and another with four-sublattice Néel-II order for κ >κc 2=0.340 (5 ) . Two different paramagnetic phases are found to exist in the intermediate region. Over the range κc1<κ<κci=0.305 (5 ) we find a gapless phase with no discernible magnetic order, which is a strong candidate for being a quantum spin liquid, while over the range κci<κ <κc 2 we find a gapped phase, which is most likely a lattice nematic with staggered dimer VBC order that breaks the lattice rotational symmetry.

Neural Network Modeling of UH-60A Pilot Vibration

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi

2003-01-01

Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

Performing a scatterv operation on a hierarchical tree network optimized for collective operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D

Performing a scatterv operation on a hierarchical tree network optimized for collective operations including receiving, by the scatterv module installed on the node, from a nearest neighbor parent above the node a chunk of data having at least a portion of data for the node; maintaining, by the scatterv module installed on the node, the portion of the data for the node; determining, by the scatterv module installed on the node, whether any portions of the data are for a particular nearest neighbor child below the node or one or more other nodes below the particular nearest neighbor child; andmore » sending, by the scatterv module installed on the node, those portions of data to the nearest neighbor child if any portions of the data are for a particular nearest neighbor child below the node or one or more other nodes below the particular nearest neighbor child.« less

Quantifying specific capacity and salinity variability in Amman Zarqa Basin, Central Jordan, using empirical statistical and geostatistical techniques.

PubMed

Shaqour, F; Taany, R; Rimawi, O; Saffarini, G

2016-01-01

Modeling groundwater properties is an important tool by means of which water resources management can judge whether these properties are within the safe limits or not. This is usually done regularly and in the aftermath of crises that are expected to reflect negatively on groundwater properties, as occurred in Jordan due to crises in neighboring countries. In this study, specific capacity and salinity of groundwater of B2/A7 aquifer in Amman Zarqa Basin were evaluated to figure out the effect of population increase in this basin as a result of refugee flux from neighboring countries to this heavily populated basin after Gulf crises 1990 and 2003. Both properties were found to exhibit a three-parameter lognormal distribution. The empirically calculated β parameter of this distribution mounted up to 0.39 m(3)/h/min for specific capacity and 238 ppm for salinity. This parameter is suggested to account for the global changes that took place all over the basin during the entire period of observation and not for local changes at every well or at certain localities in the basin. It can be considered as an exploratory result of data analysis. Formal and implicit evaluation followed this step using structural analysis and construction of experimental semivariograms that represent the spatial variability of both properties. The adopted semivariograms were then used to construct maps to illustrate the spatial variability of the properties under consideration using kriging interpolation techniques. Semivariograms show that specific capacity and salinity values are spatially dependent within 14,529 and 16,309 m, respectively. Specific capacity semivariogram exhibit a nugget effect on a small scale (324 m). This can be attributed to heterogeneity or inadequacies in measurement. Specific capacity and salinity maps show that the major changes exhibit a northwest southeast trend, near As-Samra Wastewater Treatment Plant. The results of this study suggest proper management practices.

EDDIX--a database of ionisation double differential cross sections.

PubMed

MacGibbon, J H; Emerson, S; Liamsuwan, T; Nikjoo, H

2011-02-01

The use of Monte Carlo track structure is a choice method in biophysical modelling and calculations. To precisely model 3D and 4D tracks, the cross section for the ionisation by an incoming ion, double differential in the outgoing electron energy and angle, is required. However, the double differential cross section cannot be theoretically modelled over the full range of parameters. To address this issue, a database of all available experimental data has been constructed. Currently, the database of Experimental Double Differential Ionisation Cross sections (EDDIX) contains over 1200 digitalised experimentally measured datasets from the 1960s to present date, covering all available ion species (hydrogen to uranium) and all available target species. Double differential cross sections are also presented with the aid of an eight parameter functions fitted to the cross sections. The parameters include projectile species and charge, target nuclear charge and atomic mass, projectile atomic mass and energy, electron energy and deflection angle. It is planned to freely distribute EDDIX and make it available to the radiation research community for use in the analytical and numerical modelling of track structure.

WHOLE-BODY VIBRATION EXERCISE IMPROVES FUNCTIONAL PARAMETERS IN PATIENTS WITH OSTEOGENESIS IMPERFECTA: A SYSTEMATIC REVIEW WITH A SUITABLE APPROACH.

PubMed

Sá-Caputo, Danubia C; Dionello, Carla da F; Frederico, Éric Heleno F F; Paineiras-Domingos, Laisa L; Sousa-Gonçalves, Cintia Renata; Morel, Danielle S; Moreira-Marconi, Eloá; Unger, Marianne; Bernardo-Filho, Mario

2017-01-01

Patients with osteogenesis imperfecta (OI) have abnormal bone modelling and resorption. The bone tissue adaptation and responsivity to dynamic and mechanical loading may be of therapeutic use under controlled circumstances. Improvements due to the wholebody vibration (WBV) exercises have been reported in strength, motion, gait, balance, posture and bone density in several osteopenic individuals, as in post-menopausal women or children with disabling conditions, as patients with OI. The aim of this investigation was to systematically analyse the current available literature to determine the effect of WBV exercises on functional parameters of OI patients. Three reviewers independently accessed bibliographical databases. Searches were performed in the PubMed, Scopus, Science Direct and PEDro databases using keywords related to possible interventions (including WBV) used in the management of patients with osteogenesis imperfecta . Three eligible studies were identified by searches in the analysed databases. It was concluded that WBV exercises could be an important option in the management of OI patients improving the mobility and functional parameters. However, further studies are necessary for establishing suitable protocols for these patients.

Databases for multilevel biophysiology research available at Physiome.jp.

PubMed

Asai, Yoshiyuki; Abe, Takeshi; Li, Li; Oka, Hideki; Nomura, Taishin; Kitano, Hiroaki

2015-01-01

Physiome.jp (http://physiome.jp) is a portal site inaugurated in 2007 to support model-based research in physiome and systems biology. At Physiome.jp, several tools and databases are available to support construction of physiological, multi-hierarchical, large-scale models. There are three databases in Physiome.jp, housing mathematical models, morphological data, and time-series data. In late 2013, the site was fully renovated, and in May 2015, new functions were implemented to provide information infrastructure to support collaborative activities for developing models and performing simulations within the database framework. This article describes updates to the databases implemented since 2013, including cooperation among the three databases, interactive model browsing, user management, version management of models, management of parameter sets, and interoperability with applications.

Java Web Simulation (JWS); a web based database of kinetic models.

PubMed

Snoep, J L; Olivier, B G

2002-01-01

Software to make a database of kinetic models accessible via the internet has been developed and a core database has been set up at http://jjj.biochem.sun.ac.za/. This repository of models, available to everyone with internet access, opens a whole new way in which we can make our models public. Via the database, a user can change enzyme parameters and run time simulations or steady state analyses. The interface is user friendly and no additional software is necessary. The database currently contains 10 models, but since the generation of the program code to include new models has largely been automated the addition of new models is straightforward and people are invited to submit their models to be included in the database.

LIPS database with LIPService: a microscopic image database of intracellular structures in Arabidopsis guard cells.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2013-05-16

Intracellular configuration is an important feature of cell status. Recent advances in microscopic imaging techniques allow us to easily obtain a large number of microscopic images of intracellular structures. In this circumstance, automated microscopic image recognition techniques are of extreme importance to future phenomics/visible screening approaches. However, there was no benchmark microscopic image dataset for intracellular organelles in a specified plant cell type. We previously established the Live Images of Plant Stomata (LIPS) database, a publicly available collection of optical-section images of various intracellular structures of plant guard cells, as a model system of environmental signal perception and transduction. Here we report recent updates to the LIPS database and the establishment of a database table, LIPService. We updated the LIPS dataset and established a new interface named LIPService to promote efficient inspection of intracellular structure configurations. Cell nuclei, microtubules, actin microfilaments, mitochondria, chloroplasts, endoplasmic reticulum, peroxisomes, endosomes, Golgi bodies, and vacuoles can be filtered using probe names or morphometric parameters such as stomatal aperture. In addition to the serial optical sectional images of the original LIPS database, new volume-rendering data for easy web browsing of three-dimensional intracellular structures have been released to allow easy inspection of their configurations or relationships with cell status/morphology. We also demonstrated the utility of the new LIPS image database for automated organelle recognition of images from another plant cell image database with image clustering analyses. The updated LIPS database provides a benchmark image dataset for representative intracellular structures in Arabidopsis guard cells. The newly released LIPService allows users to inspect the relationship between organellar three-dimensional configurations and morphometrical parameters.

The RECONS 25 Parsec Database: Who Are the Stars? Where Are the Planets?

NASA Astrophysics Data System (ADS)

Henry, Todd J.; Dieterich, S.; Hosey, A. D.; Ianna, P. A.; Jao, W.; Koerner, D. W.; Riedel, A. R.; Slatten, K. J.; Subasavage, J.; Winters, J. G.; RECONS

2013-01-01

Since 1994, RECONS (www.recons.org, REsearch Consortium On Nearby Stars) has been discovering and characterizing the Sun's neighbors. Nearby stars provide increased fluxes, larger astrometric perturbations, and higher probabilities for eventual resolution and detailed study of planets than similar stars at larger distances. Examination of the nearby stellar sample will reveal the prevalence and structure of solar systems, as well as the balance of Jovian and terrestrial worlds. These are the stars and planets that will ultimately be key in our search for life elsewhere. Here we outline what we know ... and what we don't know ... about the population of the nearest stars. We have expanded the original RECONS 10 pc horizon to 25 pc and are constructing a database that currently includes 2124 systems. By using the CTIO 0.9m telescope --- now operated by RECONS as part of the SMARTS Consortium --- we have published the first accurate parallaxes for 149 systems within 25 pc and currently have an additional 213 unpublished systems to add. Still, we predict that roughly two-thirds of the systems within 25 pc do not yet have accurate distance measurements. In addition to revealing the Sun's stellar neighbors, we have been using astrometric techniques to search for massive planets orbiting roughly 200 of the nearest red dwarfs. Unlike radial velocity searches, our astrometric effort is most sensitive to Jovian planets in Jovian orbits, i.e. those that span decades. We have now been monitoring stars for up to 13 years with positional accuracies of a few milliarcseconds per night. We have detected stellar and brown dwarf companions, as well as enigmatic, unseen secondaries, but have yet to reveal a single super-Jupiter ... a somewhat surprising result. In total, only 3% of stars within 25 pc are known to possess planets. It seems clear that we have a great deal of work to do to map out the stars, planets, and perhaps life in the solar neighborhood. This effort is supported by the NSF through grant AST-0908402 and via observations made possible by the SMARTS Consortium.

[A Terahertz Spectral Database Based on Browser/Server Technique].

PubMed

Zhang, Zhuo-yong; Song, Yue

2015-09-01

With the solution of key scientific and technical problems and development of instrumentation, the application of terahertz technology in various fields has been paid more and more attention. Owing to the unique characteristic advantages, terahertz technology has been showing a broad future in the fields of fast, non-damaging detections, as well as many other fields. Terahertz technology combined with other complementary methods can be used to cope with many difficult practical problems which could not be solved before. One of the critical points for further development of practical terahertz detection methods depends on a good and reliable terahertz spectral database. We developed a BS (browser/server) -based terahertz spectral database recently. We designed the main structure and main functions to fulfill practical requirements. The terahertz spectral database now includes more than 240 items, and the spectral information was collected based on three sources: (1) collection and citation from some other abroad terahertz spectral databases; (2) collected from published literatures; and (3) spectral data measured in our laboratory. The present paper introduced the basic structure and fundament functions of the terahertz spectral database developed in our laboratory. One of the key functions of this THz database is calculation of optical parameters. Some optical parameters including absorption coefficient, refractive index, etc. can be calculated based on the input THz time domain spectra. The other main functions and searching methods of the browser/server-based terahertz spectral database have been discussed. The database search system can provide users convenient functions including user registration, inquiry, displaying spectral figures and molecular structures, spectral matching, etc. The THz database system provides an on-line searching function for registered users. Registered users can compare the input THz spectrum with the spectra of database, according to the obtained correlation coefficient one can perform the searching task very fast and conveniently. Our terahertz spectral database can be accessed at http://www.teralibrary.com. The proposed terahertz spectral database is based on spectral information so far, and will be improved in the future. We hope this terahertz spectral database can provide users powerful, convenient, and high efficient functions, and could promote the broader applications of terahertz technology.

Predicting Loss-of-Control Boundaries Toward a Piloting Aid

NASA Technical Reports Server (NTRS)

Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

Design sensitivity analysis using EAL. Part 1: Conventional design parameters

NASA Technical Reports Server (NTRS)

Dopker, B.; Choi, Kyung K.; Lee, J.

1986-01-01

A numerical implementation of design sensitivity analysis of builtup structures is presented, using the versatility and convenience of an existing finite element structural analysis code and its database management system. The finite element code used in the implemenatation presented is the Engineering Analysis Language (EAL), which is based on a hybrid method of analysis. It was shown that design sensitivity computations can be carried out using the database management system of EAL, without writing a separate program and a separate database. Conventional (sizing) design parameters such as cross-sectional area of beams or thickness of plates and plane elastic solid components are considered. Compliance, displacement, and stress functionals are considered as performance criteria. The method presented is being extended to implement shape design sensitivity analysis using a domain method and a design component method.

A Randomized Controlled Trial to Measure Spillover Effects of a Combined Water, Sanitation, and Handwashing Intervention in Rural Bangladesh.

PubMed

Benjamin-Chung, Jade; Amin, Nuhu; Ercumen, Ayse; Arnold, Benjamin F; Hubbard, Alan E; Unicomb, Leanne; Rahman, Mahbubur; Luby, Stephen P; Colford, John M

2018-03-27

Water, sanitation, and handwashing interventions may confer spillover effects on neighbors of intervention recipients by interrupting pathogen transmission. We measured geographically local spillovers in WASH Benefits, a cluster-randomized trial in rural Bangladesh, by comparing outcomes among neighbors of intervention vs. control participants. WASH Benefits randomly allocated geographically-defined clusters to a compound-level intervention (chlorinated drinking water, upgraded sanitation, and handwashing promotion) or control. From January to August 2015, in 180 clusters, we enrolled 1,799 neighboring children age-matched to trial participants that would have been eligible for WASH Benefits had they been conceived slightly earlier or later. After 28 months of intervention, we quantified fecal indicator bacteria in toy rinse and drinking water samples, measured soil-transmitted helminth infections, and recorded caregiver-reported diarrhea and respiratory illness. Neighbors' characteristics were balanced across arms. The prevalence of detectable E. coli in tubewell samples was lower for neighbors of intervention vs. control trial participants (prevalence ratio = 0.83; 0.73, 0.95). There was no difference in fecal indicator bacteria prevalence between arms for other environmental samples. Prevalence was similar in neighbors of intervention vs. control participants for soil-transmitted helminth infection, diarrhea, and respiratory illness. A compound-level water, sanitation, and handwashing intervention reduced neighbors' tubewell water contamination but did not impact neighboring children's health.

Spin dynamics in the stripe-ordered buckled honeycomb lattice antiferromagnet Ba 2 NiTeO 6

DOE PAGES

Asai, Shinichiro; Soda, Minoru; Kasatani, Kazuhiro; ...

2017-09-01

We carried out inelastic neutron scattering experiments on a buckled honeycomb lattice antiferromagnet Ba 2NiTeO 6 exhibiting a stripe structure at a low temperature. Magnetic excitations are observed in the energy range of ℏω≲10 meV having an anisotropy gap of 2 meV at 2 K. We perform spin-wave calculations to identify the spin model. The obtained microscopic parameters are consistent with the location of the stripe structure in the classical phase diagram. Furthermore, the Weiss temperature independently estimated from a bulk magnetic susceptibility is consistent with the microscopic parameters. The results reveal that a competition between the nearest-neighbor and next-nearest-neighbormore » interactions that together with a relatively large single-ion magnetic anisotropy stabilize the stripe magnetic structure.« less

Spin dynamics in the stripe-ordered buckled honeycomb lattice antiferromagnet Ba 2 NiTeO 6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asai, Shinichiro; Soda, Minoru; Kasatani, Kazuhiro

We carried out inelastic neutron scattering experiments on a buckled honeycomb lattice antiferromagnet Ba 2NiTeO 6 exhibiting a stripe structure at a low temperature. Magnetic excitations are observed in the energy range of ℏω≲10 meV having an anisotropy gap of 2 meV at 2 K. We perform spin-wave calculations to identify the spin model. The obtained microscopic parameters are consistent with the location of the stripe structure in the classical phase diagram. Furthermore, the Weiss temperature independently estimated from a bulk magnetic susceptibility is consistent with the microscopic parameters. The results reveal that a competition between the nearest-neighbor and next-nearest-neighbormore » interactions that together with a relatively large single-ion magnetic anisotropy stabilize the stripe magnetic structure.« less

Analysis of glottal source parameters in Parkinsonian speech.

PubMed

Hanratty, Jane; Deegan, Catherine; Walsh, Mary; Kirkpatrick, Barry

2016-08-01

Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics of the glottal source signal in Parkinsonian speech. An experiment is conducted in which a selection of glottal parameters are tested for their ability to discriminate between healthy and Parkinsonian speech. Results for each glottal parameter are presented for a database of 50 healthy speakers and a database of 16 speakers with Parkinsonian speech symptoms. Receiver operating characteristic (ROC) curves were employed to analyse the results and the area under the ROC curve (AUC) values were used to quantify the performance of each glottal parameter. The results indicate that glottal parameters can be used to discriminate between healthy and Parkinsonian speech, although results varied for each parameter tested. For the task of separating healthy and Parkinsonian speech, 2 out of the 7 glottal parameters tested produced AUC values of over 0.9.

The Application of Determining Students’ Graduation Status of STMIK Palangkaraya Using K-Nearest Neighbors Method

NASA Astrophysics Data System (ADS)

Rusdiana, Lili; Marfuah

2017-12-01

K-Nearest Neighbors method is one of methods used for classification which calculate a value to find out the closest in distance. It is used to group a set of data such as students’ graduation status that are got from the amount of course credits taken by them, the grade point average (AVG), and the mini-thesis grade. The study is conducted to know the results of using K-Nearest Neighbors method on the application of determining students’ graduation status, so it can be analyzed from the method used, the data, and the application constructed. The aim of this study is to find out the application results by using K-Nearest Neighbors concept to determine students’ graduation status using the data of STMIK Palangkaraya students. The development of the software used Extreme Programming, since it was appropriate and precise for this study which was to quickly finish the project. The application was created using Microsoft Office Excel 2007 for the training data and Matlab 7 to implement the application. The result of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5%. It could determine the predicate graduation of 94 data used from the initial data before the processing as many as 136 data which the maximal training data was 50data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study. The results of K-Nearest Neighbors method on the application of determining students’ graduation status was 92.5% could determine the predicate graduation which is the maximal training data. The K-Nearest Neighbors method is one of methods used to group a set of data based on the closest value, so that using K-Nearest Neighbors method agreed with this study.

Reduction in Predator Defense in the Presence of Neighbors in a Colonial Fish

PubMed Central

Schädelin, Franziska C.; Fischer, Stefan; Wagner, Richard H.

2012-01-01

Predation pressure has long been considered a leading explanation of colonies, where close neighbors may reduce predation via dilution, alarming or group predator attacks. Attacking predators may be costly in terms of energy and survival, leading to the question of how neighbors contribute to predator deterrence in relationship to each other. Two hypotheses explaining the relative efforts made by neighbors are byproduct-mutualism, which occurs when breeders inadvertently attack predators by defending their nests, and reciprocity, which occurs when breeders deliberately exchange predator defense efforts with neighbors. Most studies investigating group nest defense have been performed with birds. However, colonial fish may constitute a more practical model system for an experimental approach because of the greater ability of researchers to manipulate their environment. We investigated in the colonial fish, Neolamprologus caudopunctatus, whether prospecting pairs preferred to breed near conspecifics or solitarily, and how breeders invested in anti-predator defense in relation to neighbors. In a simple choice test, prospecting pairs selected breeding sites close to neighbors versus a solitary site. Predators were then sequentially presented to the newly established test pairs, the previously established stimulus pairs or in between the two pairs. Test pairs attacked the predator eight times more frequently when they were presented on their non-neighbor side compared to between the two breeding sites, where stimulus pairs maintained high attack rates. Thus, by joining an established pair, test pairs were able to reduce their anti-predator efforts near neighbors, at no apparent cost to the stimulus pairs. These findings are unlikely to be explained by reciprocity or byproduct-mutualism. Our results instead suggest a commensal relationship in which new pairs exploit the high anti-predator efforts of established pairs, which invest similarly with or without neighbors. Further studies are needed to determine the scope of commensalism as an anti-predator strategy in colonial animals. PMID:22615741

Simulated ground-water flow in the Hueco Bolson, an alluvial-basin aquifer system near El Paso, Texas

USGS Publications Warehouse

Heywood, Charles E.; Yager, Richard M.

2003-01-01

The neighboring cities of El Paso, Texas, and Ciudad Juarez, Chihuahua, Mexico, have historically relied on ground-water withdrawals from the Hueco Bolson, an alluvial-aquifer system, to supply water to their growing populations. By 1996, ground-water drawdown exceeded 60 meters in some areas under Ciudad Juarez and El Paso. A simulation of steady-state and transient ground-water flow in the Hueco Bolson in westernmost Texas, south-central New Mexico, and northern Chihuahua, Mexico, was developed using MODFLOW-96. The model is needed by El Paso Water Utilities to evaluate strategies for obtaining the most beneficial use of the Hueco Bolson aquifer system. The transient simulation represents a period of 100 years beginning in 1903 and ending in 2002. The period 1903 through 1968 was represented with 66 annual stress periods, and the period 1969 through 2002 was represented with 408 monthly stress periods. The ground-water flow model was calibrated using MODFLOWP and UCODE. Parameter values representing aquifer properties and boundary conditions were adjusted through nonlinear regression in a transient-state simulation with 96 annual time steps to produce a model that approximated (1) 4,352 water levels measured in 292 wells from 1912 to 1995, (2) three seepage-loss rates from a reach of the Rio Grande during periods from 1979 to 1981, (3) three seepage-loss rates from a reach of the Franklin Canal during periods from 1990 to 1992, and (4) 24 seepage rates into irrigation drains from 1961 to 1983. Once a calibrated model was obtained with MODFLOWP and UCODE, the optimal parameter set was used to create an equivalent MODFLOW-96 simulation with monthly temporal discretization to improve computations of seepage from the Rio Grande and to define the flow field for a chloride-transport simulation. Model boundary conditions were modified at appropriate times during the simulation to represent changes in well pumpage, drainage of agricultural fields, and channel modifications of the Rio Grande. The model input was generated from geographic information system databases, which facilitated rapid model construction and enabled testing of several conceptualizations of hydrogeologic facies boundaries. Specific yield of unconfined layers and hydraulic conductance of Quaternary faults in the fluvial facies were the most sensitive model parameters, suggesting that ground-water flow is impeded across the fault planes.

Pollinator-mediated interactions in experimental arrays vary with neighbor identity.

PubMed

Ha, Melissa K; Ivey, Christopher T

2017-02-01

Local ecological conditions influence the impact of species interactions on evolution and community structure. We investigated whether pollinator-mediated interactions between coflowering plants vary with plant density, coflowering neighbor identity, and flowering season. We conducted a field experiment in which flowering time and floral neighborhood were manipulated in a factorial design. Early- and late-flowering Clarkia unguiculata plants were placed into arrays with C. biloba neighbors, noncongeneric neighbors, additional conspecific plants, or no additional plants as a density control. We compared whole-plant pollen limitation of seed set, pollinator behavior, and pollen deposition among treatments. Interactions mediated by shared pollinators depended on the identity of the neighbor and possibly changed through time, although flowering-season comparisons were compromised by low early-season plant survival. Interactions with conspecific neighbors were likely competitive late in the season. Interactions with C. biloba appeared to involve facilitation or neutral interactions. Interactions with noncongeners were more consistently competitive. The community composition of pollinators varied among treatment combinations. Pollinator-mediated interactions involved competition and likely facilitation, depending on coflowering neighbor. Experimental manipulation helped to reveal context-dependent variation in indirect biotic interactions. © 2017 Botanical Society of America.

Multimodal Discriminative Binary Embedding for Large-Scale Cross-Modal Retrieval.

PubMed

Wang, Di; Gao, Xinbo; Wang, Xiumei; He, Lihuo; Yuan, Bo

2016-10-01

Multimodal hashing, which conducts effective and efficient nearest neighbor search across heterogeneous data on large-scale multimedia databases, has been attracting increasing interest, given the explosive growth of multimedia content on the Internet. Recent multimodal hashing research mainly aims at learning the compact binary codes to preserve semantic information given by labels. The overwhelming majority of these methods are similarity preserving approaches which approximate pairwise similarity matrix with Hamming distances between the to-be-learnt binary hash codes. However, these methods ignore the discriminative property in hash learning process, which results in hash codes from different classes undistinguished, and therefore reduces the accuracy and robustness for the nearest neighbor search. To this end, we present a novel multimodal hashing method, named multimodal discriminative binary embedding (MDBE), which focuses on learning discriminative hash codes. First, the proposed method formulates the hash function learning in terms of classification, where the binary codes generated by the learned hash functions are expected to be discriminative. And then, it exploits the label information to discover the shared structures inside heterogeneous data. Finally, the learned structures are preserved for hash codes to produce similar binary codes in the same class. Hence, the proposed MDBE can preserve both discriminability and similarity for hash codes, and will enhance retrieval accuracy. Thorough experiments on benchmark data sets demonstrate that the proposed method achieves excellent accuracy and competitive computational efficiency compared with the state-of-the-art methods for large-scale cross-modal retrieval task.

Classification Features of US Images Liver Extracted with Co-occurrence Matrix Using the Nearest Neighbor Algorithm

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Bibicu, Dorin; Moraru, Luminita; Nicolae, Mariana Carmen

2011-12-01

Co-occurrence matrix has been applied successfully for echographic images characterization because it contains information about spatial distribution of grey-scale levels in an image. The paper deals with the analysis of pixels in selected regions of interest of an US image of the liver. The useful information obtained refers to texture features such as entropy, contrast, dissimilarity and correlation extract with co-occurrence matrix. The analyzed US images were grouped in two distinct sets: healthy liver and steatosis (or fatty) liver. These two sets of echographic images of the liver build a database that includes only histological confirmed cases: 10 images of healthy liver and 10 images of steatosis liver. The healthy subjects help to compute four textural indices and as well as control dataset. We chose to study these diseases because the steatosis is the abnormal retention of lipids in cells. The texture features are statistical measures and they can be used to characterize irregularity of tissues. The goal is to extract the information using the Nearest Neighbor classification algorithm. The K-NN algorithm is a powerful tool to classify features textures by means of grouping in a training set using healthy liver, on the one hand, and in a holdout set using the features textures of steatosis liver, on the other hand. The results could be used to quantify the texture information and will allow a clear detection between health and steatosis liver.

Beta thalassemia in 31,734 cases with HBB gene mutations: Pathogenic and structural analysis of the common mutations; Iran as the crossroads of the Middle East.

PubMed

Mahdieh, Nejat; Rabbani, Bahareh

2016-11-01

Thalassemia is one of the most common single gene disorders worldwide. Nearly 80 to 90 million with minor beta thalassemia and 60-70 thousand affected infants are born annually worldwide. A comprehensive search on several databases including PubMed, InterScience, British Library Direct, and Science Direct was performed extracting papers about mutation detection and frequency of beta thalassemia. All papers reporting on the mutation frequency of beta thalassemia patients were selected to analyze the frequency of mutations in different regions and various ethnicities. Mutations of 31,734 individuals were identified. Twenty common mutations were selected for further analysis. Genotype-phenotype correlation, interactome, and in silico analyses of the mutations were performed using available bioinformatics tools. Secondary structure prediction was achieved for two common mutations with online tools. The mutations were also common among the countries neighboring Iran, which are responsible for 71% to 98% of mutations. Computational analyses could be used in addition to segregation and expression analysis to assess the extent of pathogenicity of the variant. The genetics of beta thalassemia in Iran is more extensively heterogeneous than in neighboring countries. Some common mutations have arisen historically from Iran and moved to other populations due to population migrations. Also, due to genetic drift, the frequencies of some mutations have increased in small populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Long-Term Population-Based Genotyping Study of Mycobacterium tuberculosis Complex Isolates in the French Departments of the Americas†

PubMed Central

Brudey, Karine; Filliol, Ingrid; Ferdinand, Séverine; Guernier, Vanina; Duval, Philippe; Maubert, Bertrand; Sola, Christophe; Rastogi, Nalin

2006-01-01

The three French overseas departments of the Americas are characterized both by insular (Guadeloupe and Martinique) and continental (French Guiana) settings with a tuberculosis case detection rate that varies from less than 10 per 100,000 per year in insular areas to an estimated incidence of more than 55 per 100,000 in French Guiana. Under a long-term genotyping program, more than three-fourths of all the Mycobacterium tuberculosis isolates (n = 744) received from the three settings were fingerprinted over a 10-year period (1994 to 2003) by spoligotyping and variable number of tandem DNA repeats (VNTRs) in order to understand the current trends in their detection rates, drug resistance, and groups and subpopulations at risk of contracting the disease and to pinpoint the circulating phylogeographical clades of the bacilli. The major difference in the study populations was the nationality of the patients, with a high percentage of immigrants from high-incidence neighboring countries in French Guiana and a low but increasing percentage in the French Caribbean. The rate of recent transmission was calculated to be 49.3% in French Guiana, compared to 27.2% and 16.9% in Guadeloupe and Martinique, respectively. At the phylogeographic level, 77.9% of the isolates studied belonged to four major clades (Haarlem, Latin-American and Mediterranean, T, and X) which are already reported from neighboring Caribbean islands in an international database and may underline potential interregional transmission events. PMID:16390968

Database of Novel and Emerging Adsorbent Materials

National Institute of Standards and Technology Data Gateway

SRD 205 NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials (Web, free access)   The NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials is a free, web-based catalog of adsorbent materials and measured adsorption properties of numerous materials obtained from article entries from the scientific literature. Search fields for the database include adsorbent material, adsorbate gas, experimental conditions (pressure, temperature), and bibliographic information (author, title, journal), and results from queries are provided as a list of articles matching the search parameters. The database also contains adsorption isotherms digitized from the cataloged articles, which can be compared visually online in the web application or exported for offline analysis.

Construction of a Computerized Adaptive Testing Version of the Quebec Adaptive Behavior Scale.

ERIC Educational Resources Information Center

Tasse, Marc J.; And Others

Multilog (Thissen, 1991) was used to estimate parameters of 225 items from the Quebec Adaptive Behavior Scale (QABS). A database containing actual data from 2,439 subjects was used for the parameterization procedures. The two-parameter-logistic model was used in estimating item parameters and in the testing strategy. MicroCAT (Assessment Systems…

K-Nearest Neighbor Algorithm Optimization in Text Categorization

NASA Astrophysics Data System (ADS)

Chen, Shufeng

2018-01-01

K-Nearest Neighbor (KNN) classification algorithm is one of the simplest methods of data mining. It has been widely used in classification, regression and pattern recognition. The traditional KNN method has some shortcomings such as large amount of sample computation and strong dependence on the sample library capacity. In this paper, a method of representative sample optimization based on CURE algorithm is proposed. On the basis of this, presenting a quick algorithm QKNN (Quick k-nearest neighbor) to find the nearest k neighbor samples, which greatly reduces the similarity calculation. The experimental results show that this algorithm can effectively reduce the number of samples and speed up the search for the k nearest neighbor samples to improve the performance of the algorithm.

Centralized Routing and Scheduling Using Multi-Channel System Single Transceiver in 802.16d

NASA Astrophysics Data System (ADS)

Al-Hemyari, A.; Noordin, N. K.; Ng, Chee Kyun; Ismail, A.; Khatun, S.

This paper proposes a cross-layer optimized strategy that reduces the effect of interferences from neighboring nodes within a mesh networks. This cross-layer design relies on the routing information in network layer and the scheduling table in medium access control (MAC) layer. A proposed routing algorithm in network layer is exploited to find the best route for all subscriber stations (SS). Also, a proposed centralized scheduling algorithm in MAC layer is exploited to assign a time slot for each possible node transmission. The cross-layer optimized strategy is using multi-channel single transceiver and single channel single transceiver systems for WiMAX mesh networks (WMNs). Each node in WMN has a transceiver that can be tuned to any available channel for eliminating the secondary interference. Among the considered parameters in the performance analysis are interference from the neighboring nodes, hop count to the base station (BS), number of children per node, slot reuse, load balancing, quality of services (QoS), and node identifier (ID). Results show that the proposed algorithms significantly improve the system performance in terms of length of scheduling, channel utilization ratio (CUR), system throughput, and average end to end transmission delay.

Convergence Time and Phase Transition in a Non-monotonic Family of Probabilistic Cellular Automata

NASA Astrophysics Data System (ADS)

Ramos, A. D.; Leite, A.

2017-08-01

In dynamical systems, some of the most important questions are related to phase transitions and convergence time. We consider a one-dimensional probabilistic cellular automaton where their components assume two possible states, zero and one, and interact with their two nearest neighbors at each time step. Under the local interaction, if the component is in the same state as its two neighbors, it does not change its state. In the other cases, a component in state zero turns into a one with probability α , and a component in state one turns into a zero with probability 1-β . For certain values of α and β , we show that the process will always converge weakly to δ 0, the measure concentrated on the configuration where all the components are zeros. Moreover, the mean time of this convergence is finite, and we describe an upper bound in this case, which is a linear function of the initial distribution. We also demonstrate an application of our results to the percolation PCA. Finally, we use mean-field approximation and Monte Carlo simulations to show coexistence of three distinct behaviours for some values of parameters α and β.

Regional W-Phase Source Inversion for Moderate to Large Earthquakes in China and Neighboring Areas

NASA Astrophysics Data System (ADS)

Zhao, Xu; Duputel, Zacharie; Yao, Zhenxing

2017-12-01

Earthquake source characterization has been significantly speeded up in the last decade with the development of rapid inversion techniques in seismology. Among these techniques, the W-phase source inversion method quickly provides point source parameters of large earthquakes using very long period seismic waves recorded at teleseismic distances. Although the W-phase method was initially developed to work at global scale (within 20 to 30 min after the origin time), faster results can be obtained when seismological data are available at regional distances (i.e., Δ ≤ 12°). In this study, we assess the use and reliability of regional W-phase source estimates in China and neighboring areas. Our implementation uses broadband records from the Chinese network supplemented by global seismological stations installed in the region. Using this data set and minor modifications to the W-phase algorithm, we show that reliable solutions can be retrieved automatically within 4 to 7 min after the earthquake origin time. Moreover, the method yields stable results down to Mw = 5.0 events, which is well below the size of earthquakes that are rapidly characterized using W-phase inversions at teleseismic distances.

Time-resolved fluorescence of thioredoxin single-tryptophan mutants: modeling experimental results with minimum perturbation mapping

NASA Astrophysics Data System (ADS)

Silva, Norberto D., Jr.; Haydock, Christopher; Prendergast, Franklyn G.

1994-08-01

The time-resolved fluorescence decay of single tryptophan (Trp) proteins is typically described using either a distribution of lifetimes or a sum of two or more exponential terms. A possible interpretation for this fluorescence decay heterogeneity is the existence of different isomeric conformations of Trp about its (chi) +1) and (chi) +2) dihedral angles. Are multiple Trp conformations compatible with the remainder of the protein in its crystallographic configuration or do they require repacking of neighbor side chains? It is conceivable that isomers of the neighbor side chains interconvert slowly on the fluorescence timescale and contribute additional lifetime components to the fluorescence intensity. We have explored this possibility by performing minimum perturbation mapping simulations of Trp 28 and Trp 31 in thioredoxin (TRX) using CHARMm 22. Mappings of Trp 29 and Trp 31 give the TRX Trp residue energy landscape as a function of (chi) +1) and (chi) +2) dihedral angles. Time-resolved fluorescence intensity and anisotropy decay of mutant TRX (W28F and W31F) are measured and interpreted in light of the above simulations. Relevant observables, like order parameters and isomerization rates, can be derived from the minimum perturbation maps and compared with experiment.

Environmental influences on cooperation in social dilemmas on networks

NASA Astrophysics Data System (ADS)

Xie, Yunya; Chang, Shuhua; Yan, Ming; Zhang, Zhipeng; Wang, Xinyu

2018-02-01

Environmental influence on cooperation is a classical topic that is widely applicable to social interactions. Here, we introduce a realistic model which depends on both the payoff and the strategy of the environment. As the strategy of the environment rather than the neighbor is imitated with a probability, the model takes more attention on the comprehensive influence of the nearby neighbors. The simulation results show that the cooperation level can be widely enhanced for the prisoner's dilemma game and the snowdrift game with this environment factor. In this environmental model, the mechanism of the survival of cooperators is deeply studied, and the corresponding results can be derived. Although the survival of cooperators also depends on the formation of the cooperator clusters, the enhancement of the cooperation level can be interpreted as the accumulation effect of the transformation of defection into cooperation. Interestingly, there exists a threshold of the initial fraction of the cooperators, and the cooperation increases significantly when this threshold is reached Moreover, the square cooperative cluster is stable, and robust against different levels of the noise parameter and temptation in the strategy adoption process. This work may shed light on the mechanism of cooperation in the real world.

Competing Contact Processes on Homogeneous Networks with Tunable Clusterization

NASA Astrophysics Data System (ADS)

Rybak, Marcin; Kułakowski, Krzysztof

2013-03-01

We investigate two homogeneous networks: the Watts-Strogatz network with mean degree ⟨k⟩ = 4 and the Erdös-Rényi network with ⟨k⟩ = 10. In both kinds of networks, the clustering coefficient C is a tunable control parameter. The network is an area of two competing contact processes, where nodes can be in two states, S or D. A node S becomes D with probability 1 if at least two its mutually linked neighbors are D. A node D becomes S with a given probability p if at least one of its neighbors is S. The competition between the processes is described by a phase diagram, where the critical probability pc depends on the clustering coefficient C. For p > pc the rate of state S increases in time, seemingly to dominate in the whole system. Below pc, the majority of nodes is in the D-state. The numerical results indicate that for the Watts-Strogatz network the D-process is activated at the finite value of the clustering coefficient C, close to 0.3. On the contrary, for the Erdös-Rényi network the transition is observed at the whole investigated range of C.

An approximate, maximum terminal velocity descent to a point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisler, G.R.; Hull, D.G.

1987-01-01

No closed form control solution exists for maximizing the terminal velocity of a hypersonic glider at an arbitrary point. As an alternative, this study uses neighboring extremal theory to provide a sampled data feedback law to guide the vehicle to a constrained ground range and altitude. The guidance algorithm is divided into two parts: 1) computation of a nominal, approximate, maximum terminal velocity trajectory to a constrained final altitude and computation of the resulting unconstrained groundrange, and 2) computation of the neighboring extremal control perturbation at the sample value of flight path angle to compensate for changes in the approximatemore » physical model and enable the vehicle to reach the on-board computed groundrange. The trajectories are characterized by glide and dive flight to the target to minimize the time spent in the denser parts of the atmosphere. The proposed on-line scheme successfully brings the final altitude and range constraints together, as well as compensates for differences in flight model, atmosphere, and aerodynamics at the expense of guidance update computation time. Comparison with an independent, parameter optimization solution for the terminal velocity is excellent. 6 refs., 3 figs.« less

Structural features of small benzene clusters (C6H6)n (n ≤ 30) as investigated with the all-atom OPLS potential.

PubMed

Takeuchi, Hiroshi

2012-10-18

The structures of the simplest aromatic clusters, benzene clusters (C(6)H(6))(n), are not well elucidated. In the present study, benzene clusters (C(6)H(6))(n) (n ≤ 30) were investigated with the all-atom optimized parameters for liquid simulation (OPLS) potential. The global minima and low-lying minima of the benzene clusters were searched with the heuristic method combined with geometrical perturbations. The structural features and growth sequence of the clusters were examined by carrying out local structure analyses and structural similarity evaluation with rotational constants. Because of the anisotropic interaction between the benzene molecules, the local structures consisting of 13 molecules are considerably deviated from regular icosahedron, and the geometries of some of the clusters are inconsistent with the shapes constructed by the interior molecules. The distribution of the angle between the lines normal to two neighboring benzene rings is anisotropic in the clusters, whereas that in the liquid benzene is nearly isotropic. The geometries and energies of the low-lying configurations and the saddle points between them suggest that most of the configurations previously detected in supersonic expansions take different orientations for one to four neighboring molecules.

DNA barcoding for identifying synanthropic flesh flies (Diptera, Sarcophagidae) of Colombia.

PubMed

Buenaventura, Eliana; Valverde-Castro, César; Wolff, Marta; Triana-Chavez, Omar; Gómez-Palacio, Andrés

2018-06-01

The first step for a successful use of any insect as indicator in forensic sciences is providing a precise taxonomic identification at species level. Due to morphology-based identification of Sarcophaginae flies (Diptera, Sarcophagidae) is often difficult and requires strong taxonomic expertise, their use as forensic indicators has been limited. Consequently, molecular-based approaches have been accepted as alternative means of identification. Thus, we aimed testing the efficiency of the barcode region of the mitochondrial cytochrome oxidase subunit I (COI) gene for identification of synanthropic flesh flies of several species of the genera Peckia, Oxysarcodexia, Ravinia, and Tricharaea collected in Colombia. The 645-bp fragment of COI was amplified and aligned (215 parsimoniously informative variable sites). We calculated Kimura two-parameter genetic distances and reconstruct a Neighbor-Joining phylogenetic tree. Our Neighbor-Joining tree recovered all species as monophyletic, and confirmed a new species of the genus Ravinia as also indicated by the interspecific genetic divergences and morphological observations. We obtained a 100% of identification success. Thus, the COI barcodes showed efficiency as an alternative mean of identification of species of flesh flies collected on decaying organic matter in Colombia. Copyright © 2018 Elsevier B.V. All rights reserved.

Motor-motor interactions in ensembles of muscle myosin: using theory to connect single molecule to ensemble measurements

NASA Astrophysics Data System (ADS)

Walcott, Sam

2013-03-01

Interactions between the proteins actin and myosin drive muscle contraction. Properties of a single myosin interacting with an actin filament are largely known, but a trillion myosins work together in muscle. We are interested in how single-molecule properties relate to ensemble function. Myosin's reaction rates depend on force, so ensemble models keep track of both molecular state and force on each molecule. These models make subtle predictions, e.g. that myosin, when part of an ensemble, moves actin faster than when isolated. This acceleration arises because forces between molecules speed reaction kinetics. Experiments support this prediction and allow parameter estimates. A model based on this analysis describes experiments from single molecule to ensemble. In vivo, actin is regulated by proteins that, when present, cause the binding of one myosin to speed the binding of its neighbors; binding becomes cooperative. Although such interactions preclude the mean field approximation, a set of linear ODEs describes these ensembles under simplified experimental conditions. In these experiments cooperativity is strong, with the binding of one molecule affecting ten neighbors on either side. We progress toward a description of myosin ensembles under physiological conditions.

Resonant inelastic X-ray scattering study of spin-wave excitations in the cuprate parent compound Ca 2CuO 2Cl 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lebert, B. W.; Dean, M.; Nicolaou, A.

By means of resonant inelastic x-ray scattering at the Cu L 3 edge, we measured the spin wave dispersion along <100> and <110> in the undoped cuprate Ca 2CuO 2Cl 2. The data yields a reliable estimate of the superexchange parameter J = 135 ± 4 meV using a classical spin-1/2 2D Heisenberg model with nearest-neighbor interactions and including quantum fluctuations. Including further exchange interactions increases the estimate to J = 141 meV. The 40 meV dispersion between the magnetic Brillouin zone boundary points (1/2, 0) and (1/4, 1/4) indicates that next-nearest neighbor interactions in this compound are intermediate betweenmore » the values found in La 2CuO 4 and Sr 2CuO 2Cl 2. Here by owing to the low- Z elements composing Ca 2CuOCl 2, the present results may enable a reliable comparison with the predictions of quantum many-body calculations, which would improve our understanding of the role of magnetic excitations and of electronic correlations in cuprates.« less

Resonant inelastic X-ray scattering study of spin-wave excitations in the cuprate parent compound Ca 2CuO 2Cl 2

DOE PAGES

Lebert, B. W.; Dean, M.; Nicolaou, A.; ...

2017-04-07

By means of resonant inelastic x-ray scattering at the Cu L 3 edge, we measured the spin wave dispersion along <100> and <110> in the undoped cuprate Ca 2CuO 2Cl 2. The data yields a reliable estimate of the superexchange parameter J = 135 ± 4 meV using a classical spin-1/2 2D Heisenberg model with nearest-neighbor interactions and including quantum fluctuations. Including further exchange interactions increases the estimate to J = 141 meV. The 40 meV dispersion between the magnetic Brillouin zone boundary points (1/2, 0) and (1/4, 1/4) indicates that next-nearest neighbor interactions in this compound are intermediate betweenmore » the values found in La 2CuO 4 and Sr 2CuO 2Cl 2. Here by owing to the low- Z elements composing Ca 2CuOCl 2, the present results may enable a reliable comparison with the predictions of quantum many-body calculations, which would improve our understanding of the role of magnetic excitations and of electronic correlations in cuprates.« less

Phase diagrams and free-energy landscapes for model spin-crossover materials with antiferromagnetic-like nearest-neighbor and ferromagnetic-like long-range interactions

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-11-01

We present phase diagrams, free-energy landscapes, and order-parameter distributions for a model spin-crossover material with a two-step transition between the high-spin and low-spin states (a square-lattice Ising model with antiferromagnetic-like nearest-neighbor and ferromagnetic-like long-range interactions) [P. A. Rikvold et al., Phys. Rev. B 93, 064109 (2016), 10.1103/PhysRevB.93.064109]. The results are obtained by a recently introduced, macroscopically constrained Wang-Landau Monte Carlo simulation method [Phys. Rev. E 95, 053302 (2017), 10.1103/PhysRevE.95.053302]. The method's computational efficiency enables calculation of thermodynamic quantities for a wide range of temperatures, applied fields, and long-range interaction strengths. For long-range interactions of intermediate strength, tricritical points in the phase diagrams are replaced by pairs of critical end points and mean-field critical points that give rise to horn-shaped regions of metastability. The corresponding free-energy landscapes offer insights into the nature of asymmetric, multiple hysteresis loops that have been experimentally observed in spin-crossover materials characterized by competing short-range interactions and long-range elastic interactions.

Statistical mechanics of neocortical interactions. Derivation of short-term-memory capacity

NASA Astrophysics Data System (ADS)

Ingber, Lester

1984-06-01

A theory developed by the author to describe macroscopic neocortical interactions demonstrates that empirical values of chemical and electrical parameters of synaptic interactions establish several minima of the path-integral Lagrangian as a function of excitatory and inhibitory columnar firings. The number of possible minima, their time scales of hysteresis and probable reverberations, and their nearest-neighbor columnar interactions are all consistent with well-established empirical rules of human short-term memory. Thus, aspects of conscious experience are derived from neuronal firing patterns, using modern methods of nonlinear nonequilibrium statistical mechanics to develop realistic explicit synaptic interactions.

Hierarchical Freezing in a Lattice Model

NASA Astrophysics Data System (ADS)

Byington, Travis W.; Socolar, Joshua E. S.

2012-01-01

A certain two-dimensional lattice model with nearest and next-nearest neighbor interactions is known to have a limit-periodic ground state. We show that during a slow quench from the high temperature, disordered phase, the ground state emerges through an infinite sequence of phase transitions. We define appropriate order parameters and show that the transitions are related by renormalizations of the temperature scale. As the temperature is decreased, sublattices with increasingly large lattice constants become ordered. A rapid quench results in a glasslike state due to kinetic barriers created by simultaneous freezing on sublattices with different lattice constants.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Mitchell; Thompson, Aidan P.

The purpose of this short contribution is to report on the development of a Spectral Neighbor Analysis Potential (SNAP) for tungsten. We have focused on the characterization of elastic and defect properties of the pure material in order to support molecular dynamics simulations of plasma-facing materials in fusion reactors. A parallel genetic algorithm approach was used to efficiently search for fitting parameters optimized against a large number of objective functions. In addition, we have shown that this many-body tungsten potential can be used in conjunction with a simple helium pair potential1 to produce accurate defect formation energies for the W-Hemore » binary system.« less

The minimum distance approach to classification

NASA Technical Reports Server (NTRS)

Wacker, A. G.; Landgrebe, D. A.

1971-01-01

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Performance Evaluation of Cognitive Interference Channels Using a Spectrum Overlay Strategy

NASA Technical Reports Server (NTRS)

Knoblock, Eric J.

2018-01-01

The use of cognitive radios (CR) and cooperative communications techniques may assist in interference mitigation via sensing of the environment and dynamically altering communications parameters through the use of various mechanisms - one of which is the overlay technique. This report provides a performance analysis of an interference channel with a cognitive transceiver operating in an overlay configuration to evaluate the gains from using cognition. As shown in this report, a cognitive transceiver can simultaneously share spectrum while enhancing performance of non-cognitive nodes via knowledge of the communications channel as well as knowledge of neighboring users' modulation and coding schemes.

Undistorted 3D microstructures in SU8 formed through two-photon polymerization

NASA Astrophysics Data System (ADS)

Ohlinger, Kris; Lin, Yuankun; Poole, Zsolt; Chen, Kevin P.

2011-09-01

This paper presents the wavelength dependence of two-photon polymerization in SU-8 between 720-780 nm. The study is performed by microstructuring SU-8 through a single-shot exposure of SU-8 to 140 fs tunable laser pulses with 80 MHz repetition rate, or by laser direct writing. Two-photon absorption is closely related to one-photon absorption in pristine SU-8. By careful design of the neighboring micro-structures, or by varying wet-processing parameters during development, undistorted and unbended 3D micro-structures have been fabricated through direct laser writing.

Mean field treatment of heterogeneous steady state kinetics

NASA Astrophysics Data System (ADS)

Geva, Nadav; Vaissier, Valerie; Shepherd, James; Van Voorhis, Troy

2017-10-01

We propose a method to quickly compute steady state populations of species undergoing a set of chemical reactions whose rate constants are heterogeneous. Using an average environment in place of an explicit nearest neighbor configuration, we obtain a set of equations describing a single fluctuating active site in the presence of an averaged bath. We apply this Mean Field Steady State (MFSS) method to a model of H2 production on a disordered surface for which the activation energy for the reaction varies from site to site. The MFSS populations quantitatively reproduce the KMC results across the range of rate parameters considered.

Efficient quantum state transfer in an engineered chain of quantum bits

NASA Astrophysics Data System (ADS)

Sandberg, Martin; Knill, Emanuel; Kapit, Eliot; Vissers, Michael R.; Pappas, David P.

2016-03-01

We present a method of performing quantum state transfer in a chain of superconducting quantum bits. Our protocol is based on engineering the energy levels of the qubits in the chain and tuning them all simultaneously with an external flux bias. The system is designed to allow sequential adiabatic state transfers, resulting in on-demand quantum state transfer from one end of the chain to the other. Numerical simulations of the master equation using realistic parameters for capacitive nearest-neighbor coupling, energy relaxation, and dephasing show that fast, high-fidelity state transfer should be feasible using this method.

Ruggedness/robustness evaluation and system suitability test on United States Pharmacopoeia XXVI assay ginsenosides in Asian and American ginseng by high-performance liquid chromatography.

PubMed

Li, Yong-Guo; Chen, Ming; Chou, Gui-Xin; Wang, Zheng-Tao; Hu, Zhi-Bi

2004-09-03

The work of the ruggedness/robustness evaluation and system suitability tests was oriented to profound understand the practicability of using assay methods issued by United States Pharmacopoeia (USP XXVI and XXVII) for ginsenosides in Asian ginseng and American ginseng. The items chosen for the method validation included quantitative related items such as recovery of Rg(1) and Rb(1), respectively, and qualitative related items such as resolution, theoretical plate number, relative retention time of two critical-band-pairs, Rg(1)/Re and Rb(1) with its neighboring peak, respectively. Totally, 16 column types were used for comparison of different vendors, different packing materials, different size, etc. and five sets of LC systems and two laboratories were involved in comparing the data of both quantitative and qualitative items. The results showed that different packing materials of columns used might significantly alters separation. The column packing material Hypersil afforded the preferable separating for the ginsenosides. No significant difference was observed from the different instrumentations and inter-laboratories. Our results suggest a modification of the system suitability test as given in USP26-NF21 and the latest version of USP27-NF22, which was not suitable for most systems. Using resolutions of Rg(1)/Re and Rb(1) with its neighboring peak as critical parameters for the ginsenosides assay and omitting the relative retention time of both Rg(1)/Re and Rb(1) with its neighboring peak is our suggestion for a more reasonable, yet practicable system suitability. Six typical chromatograms gain from different columns were figured out as well.

Electronic couplings and on-site energies for hole transfer in DNA: Systematic quantum mechanical/molecular dynamic study

NASA Astrophysics Data System (ADS)

Voityuk, Alexander A.

2008-03-01

The electron hole transfer (HT) properties of DNA are substantially affected by thermal fluctuations of the π stack structure. Depending on the mutual position of neighboring nucleobases, electronic coupling V may change by several orders of magnitude. In the present paper, we report the results of systematic QM/molecular dynamic (MD) calculations of the electronic couplings and on-site energies for the hole transfer. Based on 15ns MD trajectories for several DNA oligomers, we calculate the average coupling squares ⟨V2⟩ and the energies of basepair triplets XG +Y and XA +Y, where X, Y =G, A, T, and C. For each of the 32 systems, 15 000 conformations separated by 1ps are considered. The three-state generalized Mulliken-Hush method is used to derive electronic couplings for HT between neighboring basepairs. The adiabatic energies and dipole moment matrix elements are computed within the INDO/S method. We compare the rms values of V with the couplings estimated for the idealized B-DNA structure and show that in several important cases the couplings calculated for the idealized B-DNA structure are considerably underestimated. The rms values for intrastrand couplings G-G, A-A, G-A, and A-G are found to be similar, ˜0.07eV, while the interstrand couplings are quite different. The energies of hole states G+ and A+ in the stack depend on the nature of the neighboring pairs. The XG +Y are by 0.5eV more stable than XA +Y. The thermal fluctuations of the DNA structure facilitate the HT process from guanine to adenine. The tabulated couplings and on-site energies can be used as reference parameters in theoretical and computational studies of HT processes in DNA.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gil, D.M.; Osiry, H.; Pomiro, F.

The hydrogen bond and π-π stacking are two non-covalent interactions able to support cooperative magnetic ordering between paramagnetic centers. This contribution reports the crystal structure and related magnetic properties for VO[Fe(CN){sub 5}NO]·2H{sub 2}O, which has a layered structure. This solid crystallizes with an orthorhombic unit cell, in the Pna2{sub 1} space group, with cell parameters a=14.1804(2), b=10.4935(1), c=7.1722(8) Å and four molecules per unit cell (Z=4). Its crystal structure was solved and refined from powder X-ray diffraction data. Neighboring layers remain linked through a network of hydrogen bonds involving a water molecule coordinated to the axial position for the Vmore » atom and the unbridged axial NO and CN ligands. An uncoordinated water molecule is found forming a triple bridge between these last two ligands and the coordinated water molecule. The magnetic measurements, recorded down to 2 K, shows a ferromagnetic interaction between V atoms located at neighboring layers, with a Curie-Weiss constant of 3.14 K. Such ferromagnetic behavior was interpreted as resulting from a superexchange interaction through the network of strong OH····O{sub H2O}, OH····N{sub CN}, and OH····O{sub NO} hydrogen bonds that connects neighboring layers. The interaction within the layer must be of antiferromagnetic nature and it was detected close to 2 K. - Graphical abstract: Coordination environment for the metals in vanadyl (II) nitroprusside dihydrate. Display Omitted - Highlights: • Crystal structure of vanadyl nitroprusside dehydrate. • Network of hydrogen bonds. • Magnetic interactions through a network of hydrogen bonds. • Layered transition metal nitroprussides.« less